Triple
T2175288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DocBook |
E48511
|
entity |
| Predicate | hasSchemaLanguage |
P37416
|
FINISHED |
| Object | DTD |
—
|
LITERAL 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: DTD | Statement: [DocBook, hasSchemaLanguage, DTD]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSchemaLanguage Context triple: [DocBook, hasSchemaLanguage, DTD]
-
A.
hasTypeSystem
Indicates that an entity employs, is governed by, or is associated with a particular type system (a defined set of rules for classifying and constraining types).
-
B.
hasGrammar
Indicates that an entity possesses, follows, or is associated with a particular system of grammatical rules or structure.
-
C.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
D.
hasSubstrateLanguage
Indicates a relationship where one language serves as the underlying substrate that has influenced or shaped another language.
-
E.
hasLanguageRepresentation
Indicates that an entity is expressed, encoded, or represented using a particular natural or formal language.
- F. None of above. chosen
Provenance (4 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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc1559ff481908efe3f214b2570dc |
completed | March 7, 2026, 6:10 a.m. |
| PD | Predicate disambiguation | batch_69abbd9efc1c81909a65044a1ffc9038 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abc153b22481908115e5f582c93f12 |
completed | March 7, 2026, 6:10 a.m. |
Created at: March 4, 2026, 7:45 p.m.