Triple
T5741564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hazel Krasinski |
E126625
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Hazel |
E394538
|
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: [Hazel Krasinski, givenName, Hazel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hazel Context triple: [Hazel Krasinski, givenName, Hazel]
-
A.
Hazel
chosen
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.
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.
-
D.
Hazel Tyler
Hazel Tyler is the mother of Vince Tyler, a character in the British television series "Queer as Folk."
-
E.
Zoe
"Zoe" is a 2018 science-fiction romantic drama film directed by Drake Doremus that explores love and relationships in a near-future world of advanced artificial intelligence and synthetic partners.
- 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_69c0083179548190b384b0bf3c08ca4d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0258382908190af8787feb1e5fbcd |
completed | March 22, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07e1bfe4481908740aa20d55ec8f6 |
completed | March 22, 2026, 11:41 p.m. |
Created at: March 22, 2026, 3:48 p.m.