Triple
T19980916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fair Youth |
E493812
|
entity |
| Predicate | subjectOfScholarlyDebate |
P57563
|
FINISHED |
| Object | real-life identity |
—
|
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: real-life identity | Statement: [Fair Youth, subjectOfScholarlyDebate, real-life identity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectOfScholarlyDebate Context triple: [Fair Youth, subjectOfScholarlyDebate, real-life identity]
-
A.
inAcademicDebate
Indicates that one entity is engaged in a formal, scholarly argument or discussion with another entity, typically following academic norms and methods of reasoning.
-
B.
debatedWithin
Indicates that something is discussed or argued about within a particular group, context, or domain.
-
C.
fieldOfDebate
Indicates that something is the subject or domain around which a debate or argumentative discussion is centered.
-
D.
majorDebateWith
Indicates a significant, often public or formal, debate or dispute occurring between two entities.
-
E.
debateTopic
chosen
Indicates that one entity serves as the subject or issue being discussed or argued about in a debate involving another entity.
- F. None of above.
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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65d12d968819081e315ec4585cd9f |
completed | April 20, 2026, 5:06 p.m. |
| PD | Predicate disambiguation | batch_69e537fae79c81909eae39500766d0b6 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 11, 2026, 3:28 p.m.