Triple
T6864864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keefer |
E158374
|
entity |
| Predicate | hasSpecies |
P965
|
FINISHED |
| Object | Greyhound |
E126778
|
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: Greyhound | Statement: [Keefer, hasSpecies, Greyhound]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greyhound Context triple: [Keefer, hasSpecies, Greyhound]
-
A.
Greyhound
Greyhound is a 2020 World War II naval thriller film starring Tom Hanks as a U.S. destroyer captain escorting Allied convoys across the Atlantic while evading German U-boats.
-
B.
Greyhound
chosen
Greyhound is a breed of tall, slender sighthound renowned for its exceptional speed and grace, historically used for hunting and racing.
-
C.
Hound
Hound is a coastal civil parish in the Borough of Eastleigh in Hampshire, England, encompassing villages such as Netley and Butlocks Heath.
-
D.
Saluki
The Saluki is an Amtrak passenger train service operating in the Midwest, primarily connecting Chicago with Carbondale, Illinois.
-
E.
Ridgebacks
The Ridgebacks are the varsity athletic teams representing Ontario Tech University in intercollegiate sports competitions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c68830cdbc8190a8301c7a9d9f651a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d88af6d88190ac9faa32fa1bfa0e |
completed | March 27, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c72ff153d48190a4b0d4e403457fe8 |
completed | March 28, 2026, 1:33 a.m. |
Created at: March 27, 2026, 2:21 p.m.