Triple
T38078870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colón, La Libertad, El Salvador |
E950796
|
entity |
| Predicate | capitalOfCountryDistance |
P33891
|
FINISHED |
| Object | near San Salvador |
—
|
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: near San Salvador | Statement: [Colón, La Libertad, El Salvador, capitalOfCountryDistance, near San Salvador]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capitalOfCountryDistance Context triple: [Colón, La Libertad, El Salvador, capitalOfCountryDistance, near San Salvador]
-
A.
distanceFromCapital
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.
prefecturalCapitalDistanceRelation
Indicates a spatial relationship specifying the distance between an entity and the capital city of its prefecture.
-
D.
countryCapitalNearby
chosen
Indicates that a country’s capital city is geographically close to a specified location or entity.
-
E.
departmentCapitalDistanceKm
Indicates the distance in kilometers between a department and its capital.
- 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_69f76f02a6c48190a94f3c0b3ee90cf2 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fe5ec9028081909ae3d6fbe2f4cbbc |
completed | May 8, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69fe5e1d715881909fc516fafc707644 |
completed | May 8, 2026, 10:05 p.m. |
Created at: May 3, 2026, 4:21 p.m.