Triple
T2637433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas's 30th congressional district |
E59779
|
entity |
| Predicate | notableIssueFocus |
P29037
|
FINISHED |
| Object | urban development |
—
|
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: urban development | Statement: [Texas's 30th congressional district, notableIssueFocus, urban development]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableIssueFocus Context triple: [Texas's 30th congressional district, notableIssueFocus, urban development]
-
A.
hasNotableIssue
Indicates that an entity is associated with a significant problem, concern, or defect that is noteworthy or exceptional compared to typical cases.
-
B.
knownIssue
Indicates that the subject has an issue or problem that is already identified, recognized, or documented.
-
C.
involvesIssue
chosen
Indicates that an action, event, or entity is related to, concerns, or includes a particular issue.
-
D.
majorIssue
Indicates that something is a primary or most significant problem, concern, or obstacle in a given context.
-
E.
oversightFocus
Indicates that one entity’s oversight, supervision, or monitoring activities are specifically directed toward another entity or aspect.
- 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_69ab4ac8596c8190b34997e73d9e991c |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8e3190081908ea828fe79569cc9 |
completed | March 7, 2026, 7:50 a.m. |
| PD | Predicate disambiguation | batch_69abd812849881908f956845a80e0205 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.