Triple
T60170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kathy Hochul |
E1192
|
entity |
| Predicate | isFirstFemaleHolderOfOffice |
P4487
|
FINISHED |
| Object | Governor of New York |
—
|
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: Governor of New York | Statement: [Kathy Hochul, isFirstFemaleHolderOfOffice, Governor of New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFirstFemaleHolderOfOffice Context triple: [Kathy Hochul, isFirstFemaleHolderOfOffice, Governor of New York]
-
A.
firstInOfficeTo
Indicates that one entity was the earliest or first to hold a particular office or position in relation to another entity or context.
-
B.
firstUsedInElection
Indicates that something (such as a method, technology, or rule) was used for the first time in a particular election.
-
C.
hasPresident
Indicates that an entity holds the position or role of president for another entity.
-
D.
hasChiefExecutiveRole
Indicates that an entity holds the highest executive leadership position and overall managerial authority within an organization.
-
E.
presidentElect
Indicates that one entity has been elected to be president of another entity (such as a country or organization) but has not yet assumed the office.
- F. None of above. chosen
Provenance (4 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_69a24a552ef88190a0df287d68c65cba |
completed | Feb. 28, 2026, 1:52 a.m. |
| NER | Named-entity recognition | batch_69a251a1b8ac8190b44be4c3c41e5681 |
completed | Feb. 28, 2026, 2:23 a.m. |
| PD | Predicate disambiguation | batch_69a24ea0bec48190b2af1fb287e9e692 |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a251a088f8819083797c2baf310c39 |
completed | Feb. 28, 2026, 2:23 a.m. |
Created at: Feb. 28, 2026, 1:55 a.m.