Triple
T21710752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lankaran |
E535895
|
entity |
| Predicate | distanceToCapitalApproxKm |
P117649
|
FINISHED |
| Object | 270 |
—
|
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: 270 | Statement: [Lankaran, distanceToCapitalApproxKm, 270]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToCapitalApproxKm Context triple: [Lankaran, distanceToCapitalApproxKm, 270]
-
A.
distanceFromCapital
Indicates the measured distance between a given location and the capital city of its corresponding region or country.
-
B.
distanceToProvinceCapital_km
chosen
Indicates the distance, measured in kilometers, between a given location and the capital city of its province.
-
C.
distanceFromRegionalCapital
Indicates the measured spatial distance between a given place and its corresponding regional capital.
-
D.
regionCapitalDistanceRelation
Indicates a relationship specifying the distance between a region and its capital.
-
E.
countryCapitalNearby
Indicates that a country’s capital city is geographically close to a specified location or entity.
- 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_69e0c46b44c0819088ab883ebd44e0e8 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69efb5333c8481909d729fb3bc3c9bc5 |
completed | April 27, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69e6969725bc81908e7ad19619ba2688 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:46 p.m.