Triple
T333237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas's 15th congressional district |
E6668
|
entity |
| Predicate | hasSignificantIssue |
P9106
|
FINISHED |
| Object | immigration policy |
—
|
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: immigration policy | Statement: [Texas's 15th congressional district, hasSignificantIssue, immigration policy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSignificantIssue Context triple: [Texas's 15th congressional district, hasSignificantIssue, immigration policy]
-
A.
hasNotableIssue
chosen
Indicates that an entity is associated with a significant problem, concern, or defect that is noteworthy or exceptional compared to typical cases.
-
B.
hadKeyIssue
Indicates that an entity experienced a primary or critical problem related to a key aspect, factor, or component.
-
C.
majorIssue
Indicates that something is a primary or most significant problem, concern, or obstacle in a given context.
-
D.
hasSign
Indicates that an entity possesses, displays, or is associated with a particular sign or symbol.
-
E.
hasNotableSubject
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
- 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_69a2e79434908190a9d5afe415153ad9 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eac4d9d081908a624464e450fb0e |
completed | Feb. 28, 2026, 1:16 p.m. |
| PD | Predicate disambiguation | batch_69a2e94d99cc8190a112e4b630ec63c1 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.