Triple
T17865779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Pate |
E446695
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Hondo |
—
|
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: Hondo | Statement: [Michael Pate, notableWork, Hondo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hondo Context triple: [Michael Pate, notableWork, Hondo]
-
A.
Hondo
Hondo is the nickname of John Havlicek, a Hall of Fame Boston Celtics swingman renowned for his versatility, stamina, and clutch performances in the NBA.
-
B.
Hondo
Hondo is the main worship hall of a Japanese Buddhist temple, serving as the central space for enshrining the principal deity and conducting religious ceremonies.
-
C.
Hondo
Hondo is the nickname of Frank Oliver Howard, a legendary American Major League Baseball slugger best known for his towering home runs in the 1960s and early 1970s.
-
D.
Hondo
chosen
Hondo is a 1953 Western film starring John Wayne, based on a Louis L’Amour story and noted for its rugged frontier setting and strong character-driven narrative.
-
E.
Dan "Hondo" Harrelson
Dan "Hondo" Harrelson is the tough, tactical leader of an elite Los Angeles S.W.A.T. team in the 2003 action film "S.W.A.T."
- 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_69d8b9f4c22c819093c2680434472894 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49793a2588190bb341ac606d767fe |
completed | April 19, 2026, 8:51 a.m. |
Created at: April 10, 2026, 10:17 a.m.