Triple
T12787051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sid Richardson Museum |
E305656
|
entity |
| Predicate | hasSubjectMatterInCollection |
P81453
|
FINISHED |
| Object | cowboys |
—
|
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: cowboys | Statement: [Sid Richardson Museum, hasSubjectMatterInCollection, cowboys]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubjectMatterInCollection Context triple: [Sid Richardson Museum, hasSubjectMatterInCollection, cowboys]
-
A.
hasWorkInCollection
Indicates that a work or item is included as part of a particular collection.
-
B.
hasSubdiscipline
Indicates that one discipline includes another, more specialized field of study as a subordinate branch.
-
C.
hasPartOfCorpus
Indicates that one entity constitutes a component or segment of the overall corpus associated with another entity.
-
D.
hasSeriesSubject
Indicates that a series is about, centers on, or thematically focuses on a particular subject.
-
E.
hasWorksAbout
chosen
Indicates that one entity (such as a creator, collection, or source) includes or is associated with works whose subject or focus is another entity.
- 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_69d7bdf366888190a8cccb982606889c |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e5dbdb88190a1b06721ada51627 |
completed | April 10, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69d9640ba0688190973e4e7ec8d4a8e0 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:29 p.m.