Triple
T11301999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Río San Juan |
E267616
|
entity |
| Predicate | waterUsedBySector |
P68556
|
FINISHED |
| Object | agricultural sector of Nuevo León |
—
|
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 sector of Nuevo León | Statement: [Río San Juan, waterUsedBySector, agricultural sector of Nuevo León]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterUsedBySector Context triple: [Río San Juan, waterUsedBySector, agricultural sector of Nuevo León]
-
A.
waterUse
Indicates the amount or manner in which water is consumed, utilized, or withdrawn by an entity or activity.
-
B.
reservoirUse
Indicates the way a reservoir is utilized or the purpose for which its stored water is used.
-
C.
hasWaterUse
chosen
Indicates a relationship where one entity utilizes or consumes water for a particular purpose, process, or function.
-
D.
waterSupplyShare
Indicates the proportion of a total water supply that is allocated to or used by a particular entity.
-
E.
waterQualityUse
Indicates the way in which water quality is evaluated, classified, or applied for specific purposes or uses.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9a4aad4819097384e1b591be2e3 |
completed | April 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69d787a6ca2c8190afdc24b61ccd3f8a |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.