Triple
T19489763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Novomoskovsk |
E487615
|
entity |
| Predicate | roadDistanceToMoscow_km |
P24098
|
FINISHED |
| Object | about 220 |
—
|
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 220 | Statement: [Novomoskovsk, roadDistanceToMoscow_km, about 220]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadDistanceToMoscow_km Context triple: [Novomoskovsk, roadDistanceToMoscow_km, about 220]
-
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.
distanceDirectionFromMoscow
Indicates the relative distance and compass direction of one location measured from Moscow.
-
D.
distanceToSmolensk
Indicates the spatial distance between a given entity and the location of Smolensk.
-
E.
distanceToNizhnyNovgorod
Indicates the spatial distance between a given entity and the location of Nizhny Novgorod.
- 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_69d8e8d924388190b847cb15bb3d0aff |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6348ad4088190b530f47efca90165 |
completed | April 20, 2026, 2:13 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7883308190b73912a71a35a835 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:39 p.m.