Triple
T22090582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boyd Crowder |
E545901
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Crowder |
—
|
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: Crowder | Statement: [Boyd Crowder, familyName, Crowder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Crowder Context triple: [Boyd Crowder, familyName, Crowder]
-
A.
Crowder
chosen
Crowder is a surname most prominently associated in sports with NBA player Jae Crowder.
-
B.
McCauley
McCauley is the maiden surname of Rosa Parks, the prominent American civil rights activist known for her pivotal role in the Montgomery bus boycott.
-
C.
Oakes
Oakes is a surname of English origin borne by various notable individuals, including Patricia Luisa Oakes.
-
D.
Cuyler
Cuyler is a small unincorporated community located in rural Baker County in the U.S. state of Florida.
-
E.
Cressner
Cressner is the sadistic, wealthy gambler and primary villain in Stephen King’s short story “The Ledge,” known for forcing a man to risk his life by walking around a narrow ledge high above the city.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128e53dfc81909858cdad8b09c5fb |
completed | April 28, 2026, 9:38 p.m. |
Created at: April 16, 2026, 8:29 p.m.