Triple
T8153758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gramercy Pictures |
E190391
|
entity |
| Predicate | filmTypeFocus |
P77497
|
FINISHED |
| Object | critically acclaimed films |
—
|
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: critically acclaimed films | Statement: [Gramercy Pictures, filmTypeFocus, critically acclaimed films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmTypeFocus Context triple: [Gramercy Pictures, filmTypeFocus, critically acclaimed films]
-
A.
filmType
Indicates the specific category or genre that a film belongs to.
-
B.
filmLengthFocus
Indicates that the relationship or action centers on the duration or running time of a film.
-
C.
filmTypeContext
chosen
Indicates the contextual relationship between a film and its type or category within a specific classification or usage setting.
-
D.
filmMedium
Indicates the physical or technical format (such as film stock, digital, or video) in which a film is recorded or presented.
-
E.
filmBase
Indicates the primary location or headquarters from which a film-related entity (such as a production, company, or operation) is based or operates.
- 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_69ca82bfeb6481909d07b91b5cf69f59 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb44d566b08190a6bb672f9c368806 |
completed | March 31, 2026, 3:51 a.m. |
| PD | Predicate disambiguation | batch_69cb36a0847c8190af9038aef78319b3 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:37 p.m.