Triple
T7357165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holes |
E169653
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Phoenix Pictures |
E244199
|
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: Phoenix Pictures | Statement: [Holes, productionCompany, Phoenix Pictures]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Phoenix Pictures Context triple: [Holes, productionCompany, Phoenix Pictures]
-
A.
Phoenix Pictures
chosen
Phoenix Pictures is an American film production company known for producing critically acclaimed movies such as "Black Swan" and "The Thin Red Line."
-
B.
Sun Pictures
Sun Pictures is a prominent Indian film production and distribution company best known for producing major Tamil-language blockbuster movies.
-
C.
Polygon Pictures
Polygon Pictures is a Japanese animation studio known for its 3D CGI work on numerous anime series and international co-productions.
-
D.
FlynnPictureCo.
FlynnPictureCo. is a film production company known for developing and producing major Hollywood feature films, including action and blockbuster titles.
-
E.
Snowfort Pictures
Snowfort Pictures is an independent film production company known for producing genre-driven and cult-favorite horror, thriller, and sci-fi movies.
- 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_69c68a59f2288190877ca15c19b1e822 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f13a62e48190a2d1781a630aa9f0 |
completed | March 27, 2026, 9:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7faa6a5d88190b969b7783edc67b7 |
completed | March 28, 2026, 3:58 p.m. |
Created at: March 27, 2026, 3:06 p.m.