Triple
T12401105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arthur (Inception) |
E296253
|
entity |
| Predicate | knownForScene |
P15030
|
FINISHED |
| Object | hotel hallway zero-gravity fight |
—
|
LITERAL 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: hotel hallway zero-gravity fight | Statement: [Arthur (Inception), knownForScene, hotel hallway zero-gravity fight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knownForScene Context triple: [Arthur (Inception), knownForScene, hotel hallway zero-gravity fight]
-
A.
knownForStoryline
Indicates that an entity is recognized or notable specifically for its narrative or storyline.
-
B.
namedForKnownFor
Indicates that one entity is named after another entity specifically because that other entity is notable or recognized for something.
-
C.
knownIn
Indicates that an entity is recognized, acknowledged, or familiar within a particular context, domain, or group.
-
D.
knownForGenre
Indicates that an entity is recognized or notable for working in, producing, or being associated with a particular genre.
-
E.
alsoKnownFor
chosen
Indicates that an entity is additionally recognized or noted for another work, role, achievement, or characteristic beyond its primary association.
- F. None of above.
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_69d6ad9f464c81909db36d7e96e34b9e |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e1888b48190bd750f839a26e99e |
completed | April 10, 2026, 7:23 p.m. |
| PD | Predicate disambiguation | batch_69d94d354b488190adc83fb4f2770dd5 |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:55 p.m.