Triple
T12930310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Halych |
E309358
|
entity |
| Predicate | distanceToIvanoFrankivsk |
P107074
|
FINISHED |
| Object | approximately 25 km north |
—
|
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 25 km north | Statement: [Halych, distanceToIvanoFrankivsk, approximately 25 km north]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToIvanoFrankivsk Context triple: [Halych, distanceToIvanoFrankivsk, approximately 25 km north]
-
A.
distanceToOdessa
Indicates the spatial distance between a given entity or location and the city of Odessa.
-
B.
distanceToDonetsk
Indicates the spatial distance between a given entity and the location of Donetsk.
-
C.
distanceFromBratislava_km
Indicates the distance, measured in kilometers, between a given entity’s location and the city of Bratislava.
-
D.
distanceFromVilnius
Indicates the spatial distance between an entity and the city of Vilnius.
-
E.
distanceFromTarnów
Indicates the measured spatial distance between a given location and the city of Tarnów.
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97245b6408190816d9b7e314eb51a |
completed | April 10, 2026, 9:57 p.m. |
| PD | Predicate disambiguation | batch_69d96fab4d0881909a7a4d66bab9aa85 |
completed | April 10, 2026, 9:46 p.m. |
| PDg | Predicate description generation | batch_69d970f6f5748190ad35aff801db53d5 |
completed | April 10, 2026, 9:51 p.m. |
Created at: April 9, 2026, 5:42 p.m.