Triple
T27741835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Jersey politics |
E701873
|
entity |
| Predicate | hasGubernatorialElectionCycle |
P104587
|
FINISHED |
| Object | odd-numbered years |
—
|
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: odd-numbered years | Statement: [New Jersey politics, hasGubernatorialElectionCycle, odd-numbered years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGubernatorialElectionCycle Context triple: [New Jersey politics, hasGubernatorialElectionCycle, odd-numbered years]
-
A.
governorshipElectionsHeldIn
chosen
Indicates that governorship elections are conducted or take place within a specified location or jurisdiction.
-
B.
governorTerm
Indicates the time period during which a person holds or held the office of governor of a specific jurisdiction.
-
C.
hasGovernedState
Indicates that a person or governing body has exercised official governing authority over a particular state or political territory.
-
D.
servedAsGovernorUntil
Indicates that an entity held the position of governor up to a specified end date or time.
-
E.
hadGovernor
Indicates that an administrative region or political entity was governed by a specific person who held the office of governor.
- 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_69f637169d6c8190bf74d5b882d2eb7d |
completed | May 2, 2026, 5:40 p.m. |
| PD | Predicate disambiguation | batch_69f63188e7408190af8ce8b93d128c63 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 4:11 p.m.