Triple
T27450132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheat River |
E692409
|
entity |
| Predicate | popularPutIn |
P175224
|
FINISHED |
| Object | Albright, West Virginia |
—
|
NE NERFINISHED |
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: Albright, West Virginia | Statement: [Cheat River, popularPutIn, Albright, West Virginia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: popularPutIn Context triple: [Cheat River, popularPutIn, Albright, West Virginia]
-
A.
popularFor
Indicates that something is widely liked, recognized, or favored specifically because of a particular feature, quality, or use.
-
B.
promotedIn
Indicates that an entity was advanced to a higher rank, position, or status during a specified time or event.
-
C.
popularFrom
Indicates that something gains or holds popularity starting from a specific time, source, or context.
-
D.
popular
Indicates that an entity is widely liked, admired, or favored by many people compared to alternatives.
-
E.
popularDescription
Indicates that an entity has a commonly used or widely recognized descriptive text or label associated with it.
- 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_69ef5206c9248190b5975c2a7f9d229c |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f6cee547108190ad3bc84297d8f516 |
completed | May 3, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1188708190b8f0f56e595e6057 |
completed | May 3, 2026, 4:16 a.m. |
| PDg | Predicate description generation | batch_69f6cee3604c81908a07eade2f39064e |
completed | May 3, 2026, 4:28 a.m. |
Created at: April 27, 2026, 12:47 p.m.