Triple
T621734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Helena |
E14527
|
entity |
| Predicate | distanceToContinent |
P6357
|
FINISHED |
| Object | about 1,950 km west of southwestern Africa |
—
|
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: about 1,950 km west of southwestern Africa | Statement: [Saint Helena, distanceToContinent, about 1,950 km west of southwestern Africa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToContinent Context triple: [Saint Helena, distanceToContinent, about 1,950 km west of southwestern Africa]
-
A.
distanceToContinentApproximate
chosen
Indicates an approximate measure of how far something is from a specified continent.
-
B.
closestDistanceBetweenContinents
Indicates the minimum geographical distance separating any points on two different continents.
-
C.
distanceFromMainland
Indicates the measured spatial separation between a location and the nearest point on the mainland.
-
D.
distanceToPacificOcean
Indicates the physical distance between a given location or entity and the Pacific Ocean.
-
E.
countryClosestTo
Indicates the relationship where one country is geographically nearer to a given reference point or entity than any other country.
- 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_69a4934b17c881909ace8270e8ddd202 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e3e5d80819096e72e11b533f931 |
completed | March 1, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69a49cfe9bc081909a01b4b3b48f03b7 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.