Triple
T26217705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bouira |
E655674
|
entity |
| Predicate | roadDistanceToSetif_km |
P121160
|
FINISHED |
| Object | about 170 |
—
|
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 170 | Statement: [Bouira, roadDistanceToSetif_km, about 170]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadDistanceToSetif_km Context triple: [Bouira, roadDistanceToSetif_km, about 170]
-
A.
distanceToNomeByRoad
Indicates the road travel distance between a given place and the city of Nome.
-
B.
trailDistanceApprox
Indicates that the distance along a trail between two locations is approximately a specified value, allowing for some margin of error.
-
C.
approximateRouteLength
Indicates the estimated total distance or length of a given route, rather than its exact measured value.
-
D.
roadDistanceRelation
chosen
Indicates a relationship specifying the distance between two locations as measured along a road or road network.
-
E.
roadDistanceToLeek_km
Indicates the distance in kilometers between an entity and Leek when traveling via the road network.
- 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_69ee5b4a77e08190bfcb5f8ecdc55abd |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f60d1cd19081909f7575479d6b91ca |
completed | May 2, 2026, 2:41 p.m. |
| PD | Predicate disambiguation | batch_69f5f7fd90fc81909055b211368f9139 |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 26, 2026, 8:55 p.m.