Triple
T1490359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SoftQuad Software |
E29562
|
entity |
| Predicate | field |
P3
|
FINISHED |
| Object | SGML |
E8666
|
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: SGML | Statement: [SoftQuad Software, field, SGML]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SGML Context triple: [SoftQuad Software, field, SGML]
-
A.
SGML
chosen
SGML (Standard Generalized Markup Language) is a standardized metalanguage for defining markup languages used to structure and describe the content of electronic documents.
-
B.
DSSSL
DSSSL (Document Style Semantics and Specification Language) is an ISO standard language used to define stylesheets and transformations for SGML documents, particularly in technical publishing.
-
C.
DTD
DTD (Document Type Definition) is an XML schema language used to define the legal structure, elements, and attributes of an XML document.
-
D.
XML
XML (Extensible Markup Language) is a flexible, text-based markup language designed for structuring, storing, and transporting data in a platform-independent way.
-
E.
HTM
HTM is the public transport company that operates trams and buses in and around The Hague in the Netherlands.
- 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_69a498da82e08190ba833330d05f380f |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6c233ec819087e1233af02aabfc |
completed | March 1, 2026, 11:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad1ca98e64819097916eb7717e6364 |
completed | March 8, 2026, 6:52 a.m. |
Created at: March 1, 2026, 8:12 p.m.