Triple
T32174097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden Horse Award for Best Director |
E821788
|
entity |
| Predicate | eligibleRegions |
P24526
|
FINISHED |
| Object | Chinese-speaking regions |
—
|
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: Chinese-speaking regions | Statement: [Golden Horse Award for Best Director, eligibleRegions, Chinese-speaking regions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eligibleRegions Context triple: [Golden Horse Award for Best Director, eligibleRegions, Chinese-speaking regions]
-
A.
eligibleRegion
chosen
Indicates the geographic area within which something (such as an offer, service, or rule) is valid, applicable, or permitted.
-
B.
includedRegions
Indicates that certain regions are contained within, or form part of, a larger specified region or set of regions.
-
C.
distributionRegionsInclude
Indicates that certain geographic or market regions are encompassed within the overall distribution coverage of a product or service.
-
D.
issuerRegionServed
Indicates the geographic region or area that the issuer provides services to or operates within.
-
E.
exportRegion
Indicates the region or geographic area from which goods, services, or resources are exported.
- 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_69f3490699a48190bbef96b198e8fade |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6e02ba6b881908dfafc52d3b75f1c |
completed | May 3, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69f6de09c2f481909f8b2545d3208c9f |
completed | May 3, 2026, 5:32 a.m. |
Created at: May 1, 2026, 12:34 a.m.