Triple
T2256287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas's 10th congressional district |
E49731
|
entity |
| Predicate | hasTypeOfConstituency |
P15309
|
FINISHED |
| Object | geographic |
—
|
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: geographic | Statement: [Texas's 10th congressional district, hasTypeOfConstituency, geographic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfConstituency Context triple: [Texas's 10th congressional district, hasTypeOfConstituency, geographic]
-
A.
constituencyType
chosen
Indicates the specific kind or category of electoral or representative district to which an entity belongs or refers.
-
B.
hasNumberOfConstituencies
Indicates the specific count of constituencies associated with an entity.
-
C.
electoralDistrictType
Indicates the specific category or kind of electoral district associated with an entity (e.g., federal, state, local).
-
D.
hasSeatsForConstituency
Indicates that a governing body or institution allocates or provides a certain number of representative seats for a specific constituency.
-
E.
constituency
Indicates that one entity functions as a constituent or component part within the structural or organizational makeup of 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_69a88aaa9250819095e127d0d77e8a32 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc1570dc88190bb2b17ed4c25dbb5 |
completed | March 7, 2026, 6:10 a.m. |
| PD | Predicate disambiguation | batch_69abbdb34c148190b51e99f540f97204 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.