Triple
T18007703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wigram Productions |
E430796
|
entity |
| Predicate | languageOfPrimaryWork |
P118239
|
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: [Wigram Productions, languageOfPrimaryWork, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfPrimaryWork Context triple: [Wigram Productions, languageOfPrimaryWork, English]
-
A.
primaryLanguageInWork
chosen
Indicates that a specified language is the main or predominant language used within a particular work (such as a book, film, or document).
-
B.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
-
C.
primaryLanguageIn
Indicates that a specified language is the main or official language used within a particular place, organization, or context.
-
D.
languageOfUnderlyingWork
Indicates the language in which the original or underlying work (from which a derived or related work stems) is expressed.
-
E.
hasPrimaryLanguage1
Indicates that an entity’s main or most commonly used language is the specified language.
- 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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b51d44088190bfcd35e532a4c02a |
completed | April 19, 2026, 10:57 a.m. |
| PD | Predicate disambiguation | batch_69e3f90039e4819080527f860dca042e |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:24 a.m.