Triple
T5142129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spyglass Entertainment |
E115975
|
entity |
| Predicate | hasDistributionPartners |
P61791
|
FINISHED |
| Object | major Hollywood studios |
—
|
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: major Hollywood studios | Statement: [Spyglass Entertainment, hasDistributionPartners, major Hollywood studios]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDistributionPartners Context triple: [Spyglass Entertainment, hasDistributionPartners, major Hollywood studios]
-
A.
distributionToPartners
Indicates the allocation or transfer of resources, benefits, or proceeds from a source entity to its partner entities.
-
B.
hasPartner
Indicates that one entity is in a partner relationship (such as romantic, life, or business partnership) with another entity.
-
C.
hasNetworkPartner
Indicates that an entity is connected to another entity through a formal or recognized network partnership relationship.
-
D.
segmentPartner
Indicates a partnership relationship between entities within a specific segment, context, or category.
-
E.
exportPartners
Indicates a relationship where one entity collaborates with or serves as a partner to another in exporting goods or services across borders.
- F. None of above. chosen
Provenance (4 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_69bd44459a988190a772a5c2ec6a1965 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd78d7f4d081908d59adcd86f52f1d |
completed | March 20, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69bd77ae2f10819098bb8939106e1281 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd78d6a1388190804dcf568ca92129 |
completed | March 20, 2026, 4:41 p.m. |
Created at: March 20, 2026, 1:43 p.m.