Triple
T419815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Choapa Valley |
E8074
|
entity |
| Predicate | distanceToFeature |
P7750
|
FINISHED |
| Object | close to Pacific coast |
—
|
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: close to Pacific coast | Statement: [Choapa Valley, distanceToFeature, close to Pacific coast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToFeature Context triple: [Choapa Valley, distanceToFeature, close to Pacific coast]
-
A.
flightDistance
Indicates the measured distance covered by a flight between its origin and destination.
-
B.
distanceFromTerminus
Indicates the measured distance of an entity from a defined endpoint or terminus along a route, path, or sequence.
-
C.
distance
chosen
Indicates the spatial separation or length between two points, objects, or locations.
-
D.
nearbyFeature
Indicates that one entity is located close to or in the immediate vicinity of another entity.
-
E.
distanceCategory
Indicates the qualitative classification of how far apart two entities are from each other (e.g., near, medium, far).
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eebde1d881908fb212bfba9d7c67 |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edd3b948819097d96c73d0a0f699 |
completed | Feb. 28, 2026, 1:29 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.