Triple
T27113864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden Horse Award for Best Leading Actress |
E686786
|
entity |
| Predicate | notableLanguageScope |
P74126
|
FINISHED |
| Object | Mandarin-language 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: Mandarin-language films | Statement: [Golden Horse Award for Best Leading Actress, notableLanguageScope, Mandarin-language films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableLanguageScope Context triple: [Golden Horse Award for Best Leading Actress, notableLanguageScope, Mandarin-language films]
-
A.
linguisticScope
Indicates the range or domain within language (such as a phrase, clause, or discourse segment) over which a particular linguistic element, feature, or operation has effect.
-
B.
officialLanguageScope
Indicates the scope or extent (such as region, institution, or context) within which a language holds official status.
-
C.
notableLanguageOfWorks
Indicates that a particular language is especially prominent or significant among the works created by an entity.
-
D.
hasLanguageCodeScope
Indicates that a language code is valid or applicable only within a specified scope, context, or domain.
-
E.
notableLanguageOfEligiblePrograms
chosen
Indicates that the specified language is a significant or primary language used in the programs that qualify under certain eligibility criteria.
- 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_69ef148accd48190b6ed6e13a15f2a4f |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69ff7eb7189c81909a8f73fbc4c48e02 |
completed | May 9, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69ff7e54e11081908fb5ce10c5aa7b53 |
completed | May 9, 2026, 6:35 p.m. |
Created at: April 27, 2026, 8:55 a.m.