Triple
T2790174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Friant-Kern Canal |
E61908
|
entity |
| Predicate | servesUse |
P43607
|
FINISHED |
| Object | agricultural irrigation |
—
|
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: agricultural irrigation | Statement: [Friant-Kern Canal, servesUse, agricultural irrigation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesUse Context triple: [Friant-Kern Canal, servesUse, agricultural irrigation]
-
A.
servesUsers
Indicates that an entity provides services, functionality, or benefits to one or more users.
-
B.
intendedToServe
Indicates that one entity was designed, planned, or purposed specifically to benefit, assist, or fulfill the needs of another entity.
-
C.
servesUnder
Indicates that one entity works in a subordinate role under the authority, command, or supervision of another entity.
-
D.
servesMostly
Indicates that one entity primarily functions to serve, support, or cater to another entity, more than to any other.
-
E.
servesMode
Indicates that one entity provides or operates in a particular manner, method, or mode in relation to another entity or context.
- F. None of above. chosen
Provenance (4 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_69ab4b7f51d881908768300ebd2fbdae |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdeea881481908d759c72798a50fb |
completed | March 7, 2026, 8:16 a.m. |
| PD | Predicate disambiguation | batch_69abdd025c948190a97dd961a9592bac |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abdee94c2081908e5075e87e70780a |
completed | March 7, 2026, 8:16 a.m. |
Created at: March 6, 2026, 9:58 p.m.