Triple
T31703719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States House of Representatives districts in Arizona |
E809124
|
entity |
| Predicate | gainedThirdSeat |
P172888
|
FINISHED |
| Object | post-1960 census |
—
|
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: post-1960 census | Statement: [United States House of Representatives districts in Arizona, gainedThirdSeat, post-1960 census]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gainedThirdSeat Context triple: [United States House of Representatives districts in Arizona, gainedThirdSeat, post-1960 census]
-
A.
gainedSecondSeat
Indicates that an entity has obtained a second position or seat in a governing body, organization, or representative context.
-
B.
wonFirstCommonsSeat
Indicates that an entity secured its first elected seat in the House of Commons.
-
C.
succeededInThirdTermBy
Indicates that one entity holding a position or office was followed in their third term by another specific entity as their successor.
-
D.
thirdPlaceCandidate
Indicates that the subject is the candidate who finished in third place in a competition, ranking, or election.
-
E.
hasThirdRound
Indicates that an entity includes, participates in, or is associated with a third round within a multi-round process or sequence.
- 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_69f348de914081909fc8edff56f34dbe |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6b0d21dd08190a9883ff71c94c71c |
completed | May 3, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69f6aca3dedc81908b519d53d2909868 |
completed | May 3, 2026, 2:02 a.m. |
| PDg | Predicate description generation | batch_69f6afeaaef88190aefa97e83f8db906 |
completed | May 3, 2026, 2:16 a.m. |
Created at: April 30, 2026, 11:13 p.m.