Triple
T6707427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ganthier |
E153042
|
entity |
| Predicate | geographicOrientationFromPortAuPrince |
P46910
|
FINISHED |
| Object | east |
—
|
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: east | Statement: [Ganthier, geographicOrientationFromPortAuPrince, east]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geographicOrientationFromPortAuPrince Context triple: [Ganthier, geographicOrientationFromPortAuPrince, east]
-
A.
distanceToPort-au-Prince
Indicates the spatial distance between a given location and the city of Port-au-Prince.
-
B.
geographicDirectionWithinCountry
chosen
Indicates that one place lies in a specified cardinal or intercardinal direction relative to another place within the same country.
-
C.
directionFromParis
Indicates the cardinal or relative compass direction of an entity as measured from Paris toward that entity.
-
D.
distanceFromPortOfSpain
Indicates the measured distance between a given location and the city of Port of Spain.
-
E.
geographicDirectionImpliedByName
Indicates that the name of a place or feature suggests a specific geographic direction (e.g., north, south, east, west) relative to some reference.
- 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.