Triple
T20383410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Summer Stock |
E497895
|
entity |
| Predicate | hasFilmStudioSetting |
P102864
|
FINISHED |
| Object | barn theater |
—
|
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: barn theater | Statement: [Summer Stock, hasFilmStudioSetting, barn theater]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFilmStudioSetting Context triple: [Summer Stock, hasFilmStudioSetting, barn theater]
-
A.
hasStudio
Indicates that an entity (such as a film, game, or production) is associated with or produced by a particular studio.
-
B.
hasStudiosIn
Indicates that an entity operates or maintains studio facilities located in a specified place or region.
-
C.
filmingStudio
Indicates that a studio is responsible for producing or filming a particular audiovisual work.
-
D.
hasFilmSetType
chosen
Indicates that a film or scene is associated with a particular type or category of set used in its production.
-
E.
hasFilmStyle
Indicates that a film exhibits or is characterized by a particular cinematic style or aesthetic approach.
- 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_69e0b4a5b7908190a972e4e7e698ae94 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e678b2ceec819091ad5205ee9b2174 |
completed | April 20, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69e57648be3c81908256838228cabf5c |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:27 a.m.