Triple
T16656553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VII Olympic Winter Games |
E404745
|
entity |
| Predicate | nationCount |
P56465
|
FINISHED |
| Object | 32 |
—
|
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: 32 | Statement: [VII Olympic Winter Games, nationCount, 32]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationCount Context triple: [VII Olympic Winter Games, nationCount, 32]
-
A.
countryRepresentedCount
chosen
Indicates the number of distinct countries that are represented or associated with a given entity.
-
B.
collectionCountry
Indicates the country in which an item, specimen, or data was collected.
-
C.
countryDeJure
Indicates that one entity is the legally recognized (de jure) country having sovereignty or authority over another entity.
-
D.
rangeCountries
Indicates the set of countries over which something (such as a service, product, or data coverage) is available, applicable, or valid.
-
E.
hasNumberOfCountries
Indicates the relationship that specifies how many countries are associated with or contained within a given entity.
- 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_69d8838b5fbc81908c6575c132b82e80 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37bfb2b308190bf3559df9fbb126f |
completed | April 18, 2026, 12:41 p.m. |
| PD | Predicate disambiguation | batch_69e319b1d7f08190b5ecb4a68c636c15 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:18 a.m.