Triple
T7264196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Pataki |
E159729
|
entity |
| Predicate | numberOfTermsAsGovernorOfNewYork |
P17900
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [George Pataki, numberOfTermsAsGovernorOfNewYork, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTermsAsGovernorOfNewYork Context triple: [George Pataki, numberOfTermsAsGovernorOfNewYork, 3]
-
A.
numberOfTermsAsGovernor
chosen
Indicates the number of separate terms an individual has served in the role of governor.
-
B.
numberOfGovernors
Indicates the total count of governors associated with or governing a specified entity.
-
C.
numberOfTermsAsMayor
Indicates the number of distinct terms an individual has served in the role of mayor.
-
D.
maximumNumberOfTermsForGovernor
Indicates the highest number of terms that a governor is allowed to serve in office.
-
E.
succeededBy (Governor of New York)
Indicates that one individual directly follows another in holding the office of Governor of New York.
- 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_69c68838f9948190875fd60b2351230c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb088dac8190b353f6ea3d686025 |
completed | March 27, 2026, 8:39 p.m. |
| PD | Predicate disambiguation | batch_69c6e76876608190ac4652bc7153302e |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:57 p.m.