Triple
T19043560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lionel Lindon |
E466070
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | The Oscar |
—
|
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 Oscar | Statement: [Lionel Lindon, notableWork, The Oscar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Oscar Context triple: [Lionel Lindon, notableWork, The Oscar]
-
A.
The Oscar
chosen
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.
-
B.
Milla de Oro
Milla de Oro is the main financial and commercial district of San Juan, Puerto Rico, known for its concentration of banks, corporate offices, and upscale developments.
-
C.
Oscar
Oscar is the NATO reporting name for a class of large, nuclear-powered guided-missile submarines originally built by the Soviet Navy and now operated by the Russian Navy.
-
D.
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.
-
E.
Oscar
Oscar is a masculine given name of Old English and Norse origin, commonly used in many European and English-speaking countries.
- 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_69d8dd0359648190bc2a9202c5cf29d2 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d802a75c8190a4ce45e5fbffc1b7 |
completed | April 20, 2026, 7:38 a.m. |
Created at: April 10, 2026, 12:03 p.m.