Triple
T22936253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meredith Black |
E569590
|
entity |
| Predicate | filmTitle |
P9968
|
FINISHED |
| Object | The Beaver |
—
|
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: The Beaver | Statement: [Meredith Black, filmTitle, The Beaver]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Beaver Context triple: [Meredith Black, filmTitle, The Beaver]
-
A.
The Beaver
chosen
The Beaver is a 2011 drama film starring Mel Gibson as a depressed man who begins communicating through a beaver hand puppet, directed by Jodie Foster.
-
B.
the Beaver
The Beaver is a timid yet resourceful creature and one of the central, comically earnest characters in Lewis Carroll’s nonsense poem "The Hunting of the Snark."
-
C.
Beaver
The Beaver is the official mascot of the California Institute of Technology, symbolizing the school’s emphasis on engineering, ingenuity, and industriousness.
-
D.
Beaver
Beaver is a small town in the Oklahoma Panhandle known for serving as the county seat of Beaver County and for its rural, agricultural character.
-
E.
Beaver
Beaver was one of the British ships in Boston Harbor whose tea cargo was destroyed during the Boston Tea Party protest in 1773.
- 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_69e24590862c8190858f180ad302adab |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1813608e48190922df7a5386dc391 |
completed | April 29, 2026, 3:55 a.m. |
Created at: April 17, 2026, 3:44 p.m.