Triple
T2738967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas's 33rd congressional district |
E60701
|
entity |
| Predicate | numberOfCongressionalDistrictInState |
P1679
|
FINISHED |
| Object | 33 |
—
|
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: 33 | Statement: [Texas's 33rd congressional district, numberOfCongressionalDistrictInState, 33]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCongressionalDistrictInState Context triple: [Texas's 33rd congressional district, numberOfCongressionalDistrictInState, 33]
-
A.
congressionalDistrict
Indicates that one entity is a congressional district that politically represents or geographically contains the other entity.
-
B.
numberOfRepresentatives
Indicates the quantity of representatives associated with a given entity or unit.
-
C.
numberOfDistricts
chosen
Indicates the total count of districts associated with a given entity or area.
-
D.
numberOfStatesRepresented
Indicates how many distinct states are represented or covered in a given context or entity.
-
E.
eachDistrictElects
Indicates that every electoral district selects or chooses its own representative or set of representatives.
- 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_69ab4b77febc819095603eb012cd141b |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb147a588190829b74fe05b3a114 |
completed | March 7, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69abd82859348190bce3be8f2e9d60ba |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:56 p.m.