Triple
T27210217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikitsky Monastery |
E683977
|
entity |
| Predicate | distanceFromPereslavlZalesskyCenter |
P198986
|
FINISHED |
| Object | a few kilometers |
—
|
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: a few kilometers | Statement: [Nikitsky Monastery, distanceFromPereslavlZalesskyCenter, a few kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromPereslavlZalesskyCenter Context triple: [Nikitsky Monastery, distanceFromPereslavlZalesskyCenter, a few kilometers]
-
A.
distanceFromMoscow_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Moscow.
-
B.
distanceFromSaintPetersburg
Indicates the spatial distance between a given entity and the city of Saint Petersburg.
-
C.
distanceToSmolensk
Indicates the spatial distance between a given entity and the location of Smolensk.
-
D.
railDistanceFromMoscowCenter_km
Indicates the distance in kilometers from the center of Moscow to a location when traveling by rail.
-
E.
distanceToNizhnyNovgorod
Indicates the spatial distance between a given entity and the location of Nizhny Novgorod.
- 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_69eefad339a08190aeacb2a198f1a39b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69ff1a972bf08190860696ffcd887c0f |
completed | May 9, 2026, 11:29 a.m. |
| PD | Predicate disambiguation | batch_69ff184005d88190bf38283ebc499b28 |
completed | May 9, 2026, 11:19 a.m. |
| PDg | Predicate description generation | batch_69ff1a95b6fc81909331bb03e263b5b9 |
completed | May 9, 2026, 11:29 a.m. |
Created at: April 27, 2026, 9:39 a.m.