Triple
T35411383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Texas Municipal Water District |
E1023520
|
entity |
| Predicate | servesSuburbanAreas |
P68952
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [North Texas Municipal Water District, servesSuburbanAreas, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesSuburbanAreas Context triple: [North Texas Municipal Water District, servesSuburbanAreas, true]
-
A.
servesSuburbsOf
Indicates that a service, route, or facility provides coverage or support to the suburban areas associated with a particular city or region.
-
B.
hasSuburbanService
chosen
Indicates that an entity provides or is connected to a public transportation service specifically serving suburban areas, typically linking suburbs with urban centers.
-
C.
suburbanAreasDominatedBy
Indicates that one suburban area is predominantly controlled, influenced, or characterized by another entity (such as a group, activity, or demographic).
-
D.
hasSuburbanAreas
Indicates that a place includes or is associated with surrounding residential suburban districts or neighborhoods.
-
E.
servesRemoteArea
Indicates that an entity provides services or support to people or locations in geographically remote or hard-to-reach areas.
- 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_69f76df54bac8190bd0d3b0eb35cda5f |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a00037bf4148190a58593d30efdd3f8 |
completed | May 10, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_6a0000b7af608190b718fc4111bcdad8 |
completed | May 10, 2026, 3:51 a.m. |
Created at: May 3, 2026, 4:03 p.m.