Triple
T1556191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sununu family |
E33209
|
entity |
| Predicate | hasHeldOfficeType |
P30303
|
FINISHED |
| Object | Governor of New Hampshire |
—
|
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 Hampshire | Statement: [Sununu family, hasHeldOfficeType, Governor of New Hampshire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHeldOfficeType Context triple: [Sununu family, hasHeldOfficeType, Governor of New Hampshire]
-
A.
hasOfficeHolderType
Indicates that an office or position is associated with a specific type or category of office holder (e.g., elected official, appointed official).
-
B.
heldJudicialPositionIn
Indicates that an entity served in an official judicial role or office within a specified jurisdiction or court.
-
C.
memberHoldsOffice
Indicates that a member occupies or serves in a specific official position or office within an organization or governing body.
-
D.
officePreviouslyHeldBy
Indicates that a particular office or position was formerly occupied by a specified person or entity.
-
E.
traditionallyHoldsOffice
Indicates that an entity customarily or historically occupies a particular office or position as part of an established tradition.
- 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_69a885ef9cf48190b0af0f5ce3d02231 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9407d9d1481909597af97b16512cc |
completed | March 5, 2026, 8:36 a.m. |
| PD | Predicate disambiguation | batch_69a907b688d081908171f89010c53973 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69a9407aa20881909e747f247ccec642 |
completed | March 5, 2026, 8:36 a.m. |
Created at: March 4, 2026, 7:27 p.m.