Triple
T192843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XML |
E3756
|
entity |
| Predicate | queriedWith |
P4791
|
FINISHED |
| Object |
XQuery
XQuery is a functional query and programming language designed for extracting and manipulating data from XML documents and related data sources.
|
E24282
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: XQuery | Statement: [XML, queriedWith, XQuery]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: XQuery Context triple: [XML, queriedWith, XQuery]
-
A.
XML
XML (Extensible Markup Language) is a flexible, text-based markup language designed for structuring, storing, and transporting data in a platform-independent way.
-
B.
DOM
The Document Object Model (DOM) is a platform- and language-neutral interface that represents structured documents like HTML and XML as a tree of objects, enabling programs and scripts to dynamically access and update their content and structure.
-
C.
SQL
SQL (Structured Query Language) is a standardized programming language used to manage, query, and manipulate data in relational database management systems.
-
D.
TXL
TXL was the IATA airport code for Berlin Tegel Airport, the former main international airport of Berlin, Germany.
-
E.
DAX
DAX is Germany’s leading blue-chip stock market index, tracking the performance of major companies listed on the Frankfurt Stock Exchange.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: XQuery Triple: [XML, queriedWith, XQuery]
Generated description
XQuery is a functional query and programming language designed for extracting and manipulating data from XML documents and related data sources.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: XQuery Target entity description: XQuery is a functional query and programming language designed for extracting and manipulating data from XML documents and related data sources.
-
A.
XML
XML (Extensible Markup Language) is a flexible, text-based markup language designed for structuring, storing, and transporting data in a platform-independent way.
-
B.
DOM
The Document Object Model (DOM) is a platform- and language-neutral interface that represents structured documents like HTML and XML as a tree of objects, enabling programs and scripts to dynamically access and update their content and structure.
-
C.
SQL
SQL (Structured Query Language) is a standardized programming language used to manage, query, and manipulate data in relational database management systems.
-
D.
TXL
TXL was the IATA airport code for Berlin Tegel Airport, the former main international airport of Berlin, Germany.
-
E.
DAX
DAX is Germany’s leading blue-chip stock market index, tracking the performance of major companies listed on the Frankfurt Stock Exchange.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a25bc96aa081908ef74c9827c9aa48 |
completed | Feb. 28, 2026, 3:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a30cc7d0b88190a6a7b8679af27cc5 |
completed | Feb. 28, 2026, 3:42 p.m. |
| NEDg | Description generation | batch_69a30d4e2e2c8190adeca3f64769f43b |
completed | Feb. 28, 2026, 3:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a30dbbb958819088794889968f1a0c |
completed | Feb. 28, 2026, 3:46 p.m. |
Created at: Feb. 28, 2026, 2:41 a.m.