Triple
T10544563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don DeFore |
E248780
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Hazel |
E803085
|
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: Hazel | Statement: [Don DeFore, notableWork, Hazel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hazel Context triple: [Don DeFore, notableWork, Hazel]
-
A.
Hazel
Hazel is a simple, good-hearted drifter in John Steinbeck’s novel "Cannery Row," known for his loyalty, comic misunderstandings, and unexpected moments of insight.
-
B.
Hazel
"Hazel" is a song featured on Bob Dylan’s 1974 album Planet Waves.
-
C.
Hazel
chosen
Hazel is a classic American television sitcom from the 1960s centered on a witty live-in maid and the suburban family she works for.
-
D.
Hazel
Hazel is the given first name of American Baseball Hall of Famer Kiki Cuyler.
-
E.
Lila
Lila is a central female character in Max Frisch’s novel "Mein Name sei Gantenbein," around whom the narrator constructs one of his imagined lives and relationships.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d519128cac819086c93f3bab854ac2 |
completed | April 7, 2026, 2:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9343c5c308190952596e5254b6a65 |
completed | April 10, 2026, 5:32 p.m. |
Created at: April 6, 2026, 12:32 p.m.