Triple
T11622792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hank Cochran |
E276180
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Garland |
E9807
|
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: Garland | Statement: [Hank Cochran, givenName, Garland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Garland Context triple: [Hank Cochran, givenName, Garland]
-
A.
Garland
chosen
Garland is a large suburban city in the Dallas–Fort Worth metropolitan area known for its diverse community and mixed residential, commercial, and industrial character.
-
B.
Garland
Garland is a faint dwarf galaxy that is a member of the nearby M81 Group of galaxies.
-
C.
Loudermilk
Loudermilk is a comedy-drama television series about a recovering alcoholic and former music critic with a bad attitude who reluctantly helps others in a support group while struggling with his own issues.
-
D.
Garland Greene
Garland Greene is a notorious, eerily soft-spoken serial killer character from the action film "Con Air," portrayed by Steve Buscemi.
-
E.
Doc Boone
Doc Boone is the hard-drinking yet compassionate frontier doctor character from John Ford’s classic Western film "Stagecoach."
- 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_69d6aafa51148190ab84940694c00235 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a122a3708190ab6513dad4c4fde7 |
completed | April 10, 2026, 7:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ee8762586481909a4b563c827487e0 |
completed | April 26, 2026, 9:45 p.m. |
Created at: April 8, 2026, 9:39 p.m.