Triple
T1159883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MathML |
E24468
|
entity |
| Predicate | hasVersion |
P455
|
FINISHED |
| Object | MathML 2.0 |
E24468
|
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: MathML 2.0 | Statement: [MathML, hasVersion, MathML 2.0]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MathML 2.0 Context triple: [MathML, hasVersion, MathML 2.0]
-
A.
MathML
chosen
MathML is an XML-based markup language designed to represent and structure mathematical notation for display and processing on the web.
-
B.
OpenMath
OpenMath is a standard for representing the semantic meaning of mathematical expressions in a structured, machine-readable form to enable reliable exchange between computer programs.
-
C.
ECMA-334
ECMA-334 is the ECMA International standard that formally defines the C# programming language specification.
-
D.
METS
METS (Metadata Encoding and Transmission Standard) is an XML-based standard for encoding descriptive, administrative, and structural metadata for complex digital library objects.
-
E.
Mathematical Structures of Language
Mathematical Structures of Language is a foundational work in mathematical linguistics that applies formal and algebraic methods to analyze the structure of natural languages.
- 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_69a494060e148190abb42f971242c197 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bcaf3a9081908bad2eba74dffbc1 |
completed | March 1, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac7f323bbc8190a55fe2101f9561e2 |
completed | March 7, 2026, 7:40 p.m. |
Created at: March 1, 2026, 7:45 p.m.