Triple
T9898595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OData |
E182234
|
entity |
| Predicate | usesFormat |
P130
|
FINISHED |
| Object | JSON |
E39004
|
NE FINISHED |
How this triple was built (2 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: JSON | Statement: [OData, usesFormat, JSON]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: JSON Context triple: [OData, usesFormat, JSON]
-
A.
JSON
chosen
JSON (JavaScript Object Notation) is a lightweight, text-based data interchange format widely used for transmitting structured data in web APIs and configuration files.
-
B.
JSON5
JSON5 is an extension of the JSON data format that adds more human-friendly features like comments, trailing commas, and unquoted object keys while remaining largely compatible with standard JSON.
-
C.
JSON API
JSON API is a standardized specification for building JSON-based RESTful APIs that defines how clients should request and modify resources in a consistent, structured format.
-
D.
Jakarta JSON Processing
Jakarta JSON Processing is a Jakarta EE specification that defines a standard API for parsing, generating, transforming, and querying JSON data in Java applications.
-
E.
JSONiq
JSONiq is a query and processing language designed specifically for JSON data, extending concepts from XQuery to work with hierarchical and semi-structured information.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca82876f8081909cf75df0f99bb13f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb4ac27d88190b8255f7e616f95c9 |
completed | April 2, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1eb17ed548190a2510a667dd988ca |
completed | April 5, 2026, 4:54 a.m. |
Created at: March 30, 2026, 8:40 p.m.