Triple
T6707387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arcahaie |
E153041
|
entity |
| Predicate | distanceToPortAuPrince_km |
P41202
|
FINISHED |
| Object | approximately 40 |
—
|
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: approximately 40 | Statement: [Arcahaie, distanceToPortAuPrince_km, approximately 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToPortAuPrince_km Context triple: [Arcahaie, distanceToPortAuPrince_km, approximately 40]
-
A.
distanceToPort-au-Prince
chosen
Indicates the spatial distance between a given location and the city of Port-au-Prince.
-
B.
distanceFromPortOfSpain
Indicates the measured distance between a given location and the city of Port of Spain.
-
C.
distanceFromCharlotteAmalie
Indicates the measured distance between a given location and Charlotte Amalie.
-
D.
distanceToLomé
Indicates the spatial distance between a given entity or location and the city of Lomé.
-
E.
distanceFromMauritius
Indicates the spatial distance between a given entity and the location of Mauritius.
- 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_69c68808d8d8819087369015270788fe |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d16897e48190b43eda2206b14d6a |
completed | March 27, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69c6d089c7488190a00853fb12f53b2a |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:06 p.m.