Triple
T5151972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Urgench |
E116214
|
entity |
| Predicate | roadDistanceToTashkent |
P62253
|
FINISHED |
| Object | approximately 1000 kilometres |
—
|
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 1000 kilometres | Statement: [Urgench, roadDistanceToTashkent, approximately 1000 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadDistanceToTashkent Context triple: [Urgench, roadDistanceToTashkent, approximately 1000 kilometres]
-
A.
distanceFromSamarkand_km
Indicates the physical distance, measured in kilometers, between a given place or entity and the city of Samarkand.
-
B.
distanceFromAlmaty_km
Indicates the distance, measured in kilometers, between a given place or object and the city of Almaty.
-
C.
distanceFromAshgabat
Indicates the measured spatial distance between a given location and the city of Ashgabat.
-
D.
distanceFrom Peshawar
Indicates the spatial distance between a given location or entity and the city of Peshawar.
-
E.
distanceFromMoscow_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Moscow.
- 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_69bd445d94788190b72e2cc563120995 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd79c1354c81908176703b4853c1a4 |
completed | March 20, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69bd77b0fbb88190851e2d7ae1bdcc09 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd79bf9b088190a556dc02f10204e4 |
completed | March 20, 2026, 4:45 p.m. |
Created at: March 20, 2026, 1:44 p.m.