Triple
T14183341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden Bear for Best Film |
E351511
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Golden Bear |
E70477
|
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: Golden Bear | Statement: [Golden Bear for Best Film, alsoKnownAs, Golden Bear]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Golden Bear Context triple: [Golden Bear for Best Film, alsoKnownAs, Golden Bear]
-
A.
Golden Bear
Golden Bear is the mascot representing Western New England University’s athletic teams and school spirit.
-
B.
Golden Bear
chosen
The Golden Bear is the top prize awarded to the best film at the prestigious Berlin International Film Festival, one of the world’s major annual film festivals.
-
C.
Golden Lion
The Golden Lion is the top prize awarded for the best film at the prestigious Venice Film Festival.
-
D.
The Oscar
The Oscar is a 1966 American drama film about the ruthless rise and moral downfall of a Hollywood actor, noted for its melodramatic portrayal of the film industry.
-
E.
Oscar
The Oscar is a prestigious film industry award presented annually by the Academy of Motion Picture Arts and Sciences to honor outstanding cinematic achievements.
- 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61cc0a848190b660095972b1223b |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf8114774819094670dd800a40796 |
completed | May 7, 2026, 8:37 p.m. |
Created at: April 10, 2026, 1:03 a.m.