Triple
T24267260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California's 7th congressional district |
E604872
|
entity |
| Predicate | hasNotablePastRepresentative |
P67246
|
FINISHED |
| Object | Ami Bera |
—
|
NE NERFINISHED |
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: Ami Bera | Statement: [California's 7th congressional district, hasNotablePastRepresentative, Ami Bera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotablePastRepresentative Context triple: [California's 7th congressional district, hasNotablePastRepresentative, Ami Bera]
-
A.
hasHistoricalPartyRepresentation
Indicates that an entity has been represented or affiliated with a particular political party at some point in its history.
-
B.
hasFormerHighRepresentative
Indicates that an entity previously held the role of High Representative for another entity or organization.
-
C.
hasCityRepresented
Indicates that an entity (such as a representative or organization) is associated with or represents a specific city.
-
D.
hasHistoricalOfficeHolder
chosen
Indicates that an office, position, or role has been held by a specific person at some point in the past.
-
E.
hasRepresented
Indicates that one entity has acted or served as an official representative or agent for another entity.
- 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_69e29544c29c8190b023606eafe5d36a |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28d55b4708190ad819403011cf64f |
completed | April 29, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69f1c450aa508190bc9d372a5f6ee47a |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:06 a.m.