Triple
T13125082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dallas–Fort Worth water supply system |
E311824
|
entity |
| Predicate | usesWaterSourceType |
P11699
|
FINISHED |
| Object | surface water |
—
|
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: surface water | Statement: [Dallas–Fort Worth water supply system, usesWaterSourceType, surface water]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesWaterSourceType Context triple: [Dallas–Fort Worth water supply system, usesWaterSourceType, surface water]
-
A.
waterSourceType
chosen
Indicates the kind or category of source from which water is obtained.
-
B.
waterType
Indicates the specific kind or category of water associated with an entity (e.g., fresh, salt, brackish).
-
C.
hasWaterUse
Indicates a relationship where one entity utilizes or consumes water for a particular purpose, process, or function.
-
D.
waterSource
Indicates that one entity serves as the source or provider of water for another entity.
-
E.
usesWaterTreatment
Indicates that an entity applies or relies on a water treatment process or system in its operations or activities.
- 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_69d806a9fe888190b081e2d9ea665d6c |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9819946808190b41335fb1054accd |
completed | April 10, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69d98043a74c81908648e6cd0b4c7f71 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:07 p.m.