Triple
T38662438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhōnghuá Mínguó Guóqìngrì |
E940367
|
entity |
| Predicate | numericalRepresentation |
P8195
|
FINISHED |
| Object | 10-10 |
—
|
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: 10-10 | Statement: [Zhōnghuá Mínguó Guóqìngrì, numericalRepresentation, 10-10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numericalRepresentation Context triple: [Zhōnghuá Mínguó Guóqìngrì, numericalRepresentation, 10-10]
-
A.
numericPartRepresents
Indicates that a numeric component of something stands for or encodes a specific value, property, or aspect of that thing.
-
B.
usesNumeralsFrom
Indicates that one writing system, notation, or representation employs the numeral symbols originating from another system.
-
C.
numericalProperty
Indicates that an entity is associated with a specific numeric value or measurable quantity.
-
D.
numberDescribedAs
Indicates that a number is characterized, labeled, or referred to using a particular description or phrase.
-
E.
number
chosen
Indicates that one entity is associated with a specific numerical value or count in relation to another entity or context.
- 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_69f76edfde348190bf6529d9f49ecd62 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:33 p.m.