Triple
T38037897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York State Hecht–Calandra Act |
E949399
|
entity |
| Predicate | policyDebateContext |
P137782
|
FINISHED |
| Object | school segregation in New York City |
—
|
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: school segregation in New York City | Statement: [New York State Hecht–Calandra Act, policyDebateContext, school segregation in New York City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: policyDebateContext Context triple: [New York State Hecht–Calandra Act, policyDebateContext, school segregation in New York City]
-
A.
fieldOfDebate
Indicates that something is the subject or domain around which a debate or argumentative discussion is centered.
-
B.
basisOfDebate
Indicates that one entity serves as the main reason, topic, or foundation for a debate involving another entity.
-
C.
settingOfDebate
chosen
Indicates the context, environment, or circumstances in which a particular debate takes place.
-
D.
debateTopic
Indicates that one entity serves as the subject or issue being discussed or argued about in a debate involving another entity.
-
E.
inspiredPolicyDebate
Indicates that one entity’s ideas, actions, or statements sparked or significantly influenced a policy 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_69f76eff0bb0819084bc4e63997bd039 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fd2cf39b0c8190811b8a6fa9410560 |
completed | May 8, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69fd2ad8dd988190a9899701ba00d917 |
completed | May 8, 2026, 12:14 a.m. |
Created at: May 3, 2026, 4:20 p.m.