Triple
T6358982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beslan Airport |
E143061
|
entity |
| Predicate | distanceToVladikavkaz |
P70181
|
FINISHED |
| Object | approximately 15 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: approximately 15 km | Statement: [Beslan Airport, distanceToVladikavkaz, approximately 15 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToVladikavkaz Context triple: [Beslan Airport, distanceToVladikavkaz, approximately 15 km]
-
A.
distanceToGrozny_km
Indicates the physical distance, measured in kilometers, between a given location and the city of Grozny.
-
B.
distanceFromKutaisi
Indicates the spatial distance measured from the location of Kutaisi to another specified place or entity.
-
C.
distanceToKutaisi_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Kutaisi.
-
D.
distanceFromMoscow_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Moscow.
-
E.
distanceFrom Tbilisi
Indicates the spatial distance between a given location or entity and the city of Tbilisi.
- 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_69c008d7a9c4819098d647ec47776917 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c067f72f8481908f9df0c0cdf22a52 |
completed | March 22, 2026, 10:06 p.m. |
| PD | Predicate disambiguation | batch_69c060ec091c8190912aac44e1b8b1c9 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623bb29081908bfdfb84a07ece90 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:32 p.m.