Triple
T8837386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pecos River |
E210298
|
entity |
| Predicate | waterQualityIssue |
P25191
|
FINISHED |
| Object | high salinity |
—
|
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: high salinity | Statement: [Pecos River, waterQualityIssue, high salinity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterQualityIssue Context triple: [Pecos River, waterQualityIssue, high salinity]
-
A.
waterQualityIssues
chosen
Indicates that there are problems or concerns with the condition, safety, or suitability of a water source.
-
B.
waterAppearance
Indicates how the water involved in the situation looks or visually appears (e.g., its color, clarity, or surface condition).
-
C.
waterQualityProtection
Indicates efforts, measures, or responsibilities aimed at preserving or improving the cleanliness, safety, and ecological integrity of water resources.
-
D.
waterQualityUse
Indicates the way in which water quality is evaluated, classified, or applied for specific purposes or uses.
-
E.
waterQualityImprovedAfter
Indicates that the quality of water in a given context has become better following a specified event, time, or intervention.
- 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_69ca8388549c819095fd94eadefbb007 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc606adde08190825dbdabd199c025 |
completed | April 1, 2026, 12:01 a.m. |
| PD | Predicate disambiguation | batch_69cc5c25b874819084c9ba391703e066 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:48 p.m.