Triple
T11733122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Selznick Releasing Organization |
E278949
|
entity |
| Predicate | hasLanguageOfBusiness |
P35567
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Selznick Releasing Organization, hasLanguageOfBusiness, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfBusiness Context triple: [Selznick Releasing Organization, hasLanguageOfBusiness, English]
-
A.
hasLanguageOfOrders
Indicates that one entity uses or is associated with a particular language for issuing orders or commands to another entity.
-
B.
hasPrimaryLanguageOfOperations
Indicates that an entity conducts its main activities or operations primarily using a specified language.
-
C.
languageOfCommunications
Indicates that a specified language is used as the medium for communications associated with an entity or interaction.
-
D.
hasLanguages
chosen
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
E.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
- 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_69d6aaffec6881908bead509e8621742 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4daa7f48190896fc7653e9dd70b |
completed | April 10, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69d88a7f51248190bf492bd7509b5413 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.