Triple
T8872915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Gola |
E211204
|
entity |
| Predicate | politicalOfficeHeld |
P62332
|
FINISHED |
| Object | member of the Pennsylvania House of Representatives |
—
|
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: member of the Pennsylvania House of Representatives | Statement: [Tom Gola, politicalOfficeHeld, member of the Pennsylvania House of Representatives]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: politicalOfficeHeld Context triple: [Tom Gola, politicalOfficeHeld, member of the Pennsylvania House of Representatives]
-
A.
heldPoliticalOfficeIn
chosen
Indicates that an entity served in a political office or position within a specified governmental body or jurisdiction.
-
B.
electedOffice
Indicates that an entity holds or has held a particular office or position as a result of an election.
-
C.
isPoliticalOffice
Indicates that the subject is a formal governmental or political position held within a public institution or authority.
-
D.
topPoliticalOffice
Indicates that the subject holds or is associated with the highest-ranking political office within a given governmental or political system.
-
E.
hasHeldOfficeType
Indicates that an entity has at some time occupied or served in a specified type or category of office or position.
- 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_69ca838e78748190934d82db3104f855 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc612952348190856d6964122c3f01 |
completed | April 1, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2956788190a311c647b4da17a6 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:52 p.m.