Triple
T8019265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York City specialized high schools |
E186696
|
entity |
| Predicate | policyDebateTopic |
P57619
|
FINISHED |
| Object | educational equity 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: educational equity in New York City | Statement: [New York City specialized high schools, policyDebateTopic, educational equity in New York City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: policyDebateTopic Context triple: [New York City specialized high schools, policyDebateTopic, educational equity in New York City]
-
A.
debateTopic
Indicates that one entity serves as the subject or issue being discussed or argued about in a debate involving another entity.
-
B.
mainDebateTopic
chosen
Indicates that a specified subject or issue is the primary focus or central topic of a particular debate or discussion.
-
C.
fieldOfDebate
Indicates that something is the subject or domain around which a debate or argumentative discussion is centered.
-
D.
partOfDebate
Indicates that one entity is a component, segment, or participant within a larger debate or argumentative exchange.
-
E.
canDebate
Indicates that one entity has the ability or permission to engage in a debate or argumentative discussion with 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_69ca82ac7fc081909b1398cf025423af |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3e8bc90081909f6f5878e6f1f241 |
completed | March 31, 2026, 3:24 a.m. |
| PD | Predicate disambiguation | batch_69cb049253d08190bafcecfde493ab8b |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:20 p.m.