Triple
T27741817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Jersey politics |
E701873
|
entity |
| Predicate | policyDebateTopics |
P148602
|
FINISHED |
| Object | property taxes |
—
|
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: property taxes | Statement: [New Jersey politics, policyDebateTopics, property taxes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: policyDebateTopics Context triple: [New Jersey politics, policyDebateTopics, property taxes]
-
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
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.
majorDebateWith
Indicates a significant, often public or formal, debate or dispute occurring between two entities.
-
E.
policyTopic
chosen
Indicates that one entity is about, concerned with, or categorized under a particular policy-related subject or theme.
- 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_69ef6a53c7388190899baa6daf42301c |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 27, 2026, 4:11 p.m.