Triple
T29076615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Livno |
E735956
|
entity |
| Predicate | distanceToSplitByRoad_km |
P202219
|
FINISHED |
| Object | approximately 90 |
—
|
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 90 | Statement: [Livno, distanceToSplitByRoad_km, approximately 90]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToSplitByRoad_km Context triple: [Livno, distanceToSplitByRoad_km, approximately 90]
-
A.
distanceFromRoads
Indicates the measured or estimated spatial distance between a location and the nearest road.
-
B.
distanceToNomeByRoad
Indicates the road travel distance between a given place and the city of Nome.
-
C.
tourDistanceApproxKm
Indicates an approximate total distance, measured in kilometers, covered during a tour or journey.
-
D.
roadDistanceRelation
Indicates a relationship specifying the distance between two locations as measured along a road or road network.
-
E.
isRemoteByRoad
Indicates that one location is difficult or time-consuming to reach from another when traveling by road.
- F. None of above. chosen
Provenance (4 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_69f077e9b0a48190bb79548279cb7f64 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_6a006417d1f4819093b2da02dbf2ab22 |
completed | May 10, 2026, 10:55 a.m. |
| PD | Predicate disambiguation | batch_6a00634a7a748190ac4774493fce3d30 |
completed | May 10, 2026, 10:51 a.m. |
| PDg | Predicate description generation | batch_6a006416f78081909b6ef047c531158d |
completed | May 10, 2026, 10:55 a.m. |
Created at: April 28, 2026, 10:23 a.m.