Triple
T31682857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shahdag Mountain Resort |
E808579
|
entity |
| Predicate | approxDistanceFromBaku |
P144635
|
FINISHED |
| Object | about 200 km |
—
|
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 200 km | Statement: [Shahdag Mountain Resort, approxDistanceFromBaku, about 200 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approxDistanceFromBaku Context triple: [Shahdag Mountain Resort, approxDistanceFromBaku, about 200 km]
-
A.
distanceFromBaku
chosen
Indicates the measured distance between a given place or object and the city of Baku.
-
B.
distanceFromAshgabat
Indicates the measured spatial distance between a given location and the city of Ashgabat.
-
C.
distanceToStepanakert_km
Indicates the physical distance, measured in kilometers, between a given location and Stepanakert.
-
D.
distanceFrom Tbilisi
Indicates the spatial distance between a given location or entity and the city of Tbilisi.
-
E.
distanceFromBatumi
Indicates the measured spatial distance between a given location or entity and the city of Batumi.
- 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_69f348dcf5d48190ac25b1365ae717a8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe766490c081908c49c8cc07d0ae9b |
completed | May 8, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69fe75bb5f4481908572a5ffcbdc5154 |
completed | May 8, 2026, 11:46 p.m. |
Created at: April 30, 2026, 11:05 p.m.