Triple
T29044870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huemul Island |
E738105
|
entity |
| Predicate | hasCountryCapitalDistance |
P10889
|
FINISHED |
| Object | far from Buenos Aires |
—
|
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: far from Buenos Aires | Statement: [Huemul Island, hasCountryCapitalDistance, far from Buenos Aires]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCountryCapitalDistance Context triple: [Huemul Island, hasCountryCapitalDistance, far from Buenos Aires]
-
A.
distanceFromCapital
chosen
Indicates the measured distance between a given location and the capital city of its corresponding region or country.
-
B.
regionCapitalDistanceRelation
Indicates a relationship specifying the distance between a region and its capital.
-
C.
countryLargestCityDistanceApprox
Indicates an approximate distance between a country and its largest city.
-
D.
prefecturalCapitalDistanceRelation
Indicates a spatial relationship specifying the distance between an entity and the capital city of its prefecture.
-
E.
countryCapitalNearby
Indicates that a country’s capital city is geographically close to a specified location or 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_69f077efb3848190b41574e1670f6ae2 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_6a002ae74da08190a4b47e0ff0f7f8fe |
completed | May 10, 2026, 6:51 a.m. |
| PD | Predicate disambiguation | batch_6a0029cc369c81909578e52c4a75ab18 |
completed | May 10, 2026, 6:46 a.m. |
Created at: April 28, 2026, 10:04 a.m.