Triple
T37375500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aggregate Films |
E927968
|
entity |
| Predicate | productionFor |
P23178
|
FINISHED |
| Object | Netflix |
—
|
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: Netflix | Statement: [Aggregate Films, productionFor, Netflix]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: productionFor Context triple: [Aggregate Films, productionFor, Netflix]
-
A.
productionBy
Indicates that something is created, manufactured, or generated by a particular agent, organization, or process.
-
B.
produces
Indicates that one entity creates, generates, or yields another entity as a result or output.
-
C.
producesFor
chosen
Indicates that one entity creates, manufactures, or generates something specifically intended for another entity’s use, benefit, or distribution.
-
D.
productionPurpose
Indicates that something is created, manufactured, or produced specifically for a particular use, goal, or intended function.
-
E.
productionCategory
Indicates the classification or type of production process, output, or activity that an entity is associated with.
- 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_69f76eb820248190a5c395ca50ad002a |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff29d831b881908d485609e0fc1d0b |
completed | May 9, 2026, 12:34 p.m. |
| PD | Predicate disambiguation | batch_69ff28f9f9e4819087f3402735de66c7 |
completed | May 9, 2026, 12:30 p.m. |
Created at: May 3, 2026, 4:16 p.m.