Triple
T27398073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Sandy Creek |
E691745
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object |
Cheat River watershed
The Cheat River watershed is a river basin in northern West Virginia and southwestern Pennsylvania that drains a rugged, largely forested Appalachian landscape and supports significant whitewater recreation, wildlife habitat, and regional water resources.
|
E1778900
|
NE 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: Cheat River watershed | Statement: [Big Sandy Creek, partOf, Cheat River watershed]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Cheat River watershed Triple: [Big Sandy Creek, partOf, Cheat River watershed]
Generated description
The Cheat River watershed is a river basin in northern West Virginia and southwestern Pennsylvania that drains a rugged, largely forested Appalachian landscape and supports significant whitewater recreation, wildlife habitat, and regional water resources.
Provenance (5 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_69ef5204f7048190bf226a129858fc5b |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f62cb1619481909e4f7391df3c6837 |
completed | May 2, 2026, 4:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a12c59509e8819086665762accbb91e |
completed | May 24, 2026, 9:32 a.m. |
| NEDg | Description generation | batch_6a12c69ac394819082dae768061147bd |
completed | May 24, 2026, 9:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a12c7295270819092a8b8ef0e3488a8 |
completed | May 24, 2026, 9:38 a.m. |
Created at: April 27, 2026, 12:28 p.m.