Triple
T4960248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bilibino |
E111386
|
entity |
| Predicate | distanceToMoscowApprox |
P24098
|
FINISHED |
| Object | over 6000 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: over 6000 km | Statement: [Bilibino, distanceToMoscowApprox, over 6000 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMoscowApprox Context triple: [Bilibino, distanceToMoscowApprox, over 6000 km]
-
A.
distanceFromMoscow_km
chosen
Indicates the physical distance, measured in kilometers, between a given entity’s location and Moscow.
-
B.
railDistanceFromMoscowCenter_km
Indicates the distance in kilometers from the center of Moscow to a location when traveling by rail.
-
C.
distanceFromSaintPetersburg
Indicates the spatial distance between a given entity and the city of Saint Petersburg.
-
D.
distanceToArkhangelskApproxKm
Indicates the approximate distance, measured in kilometers, between a given entity’s location and Arkhangelsk.
-
E.
distanceToYakutsk
Indicates the spatial distance between a given entity and the location of Yakutsk.
- 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_69bd4419393c819086319a6fe4bf8542 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd72e49b048190bac55d9e7a6f7963 |
completed | March 20, 2026, 4:16 p.m. |
| PD | Predicate disambiguation | batch_69bd71447fe88190bb62c5e8753da7a7 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:32 p.m.