Triple
T31495092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mielno |
E803514
|
entity |
| Predicate | distanceToKoszalin_km |
P203688
|
FINISHED |
| Object | about 12 |
—
|
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 12 | Statement: [Mielno, distanceToKoszalin_km, about 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToKoszalin_km Context triple: [Mielno, distanceToKoszalin_km, about 12]
-
A.
distanceToGdańsk_km
Indicates the physical distance, measured in kilometers, between a given place and the city of Gdańsk.
-
B.
distanceFromSzczecin_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Szczecin.
-
C.
distanceToPoznań_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Poznań.
-
D.
distanceToKraków_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Kraków.
-
E.
distanceToElbląg_km
Indicates the physical distance, measured in kilometers, between an entity and the location Elbląg.
- 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_69f348cae52081909fa8e5f697523ae3 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a01c74a72fc819084826c6c292af03a |
completed | May 11, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_6a01c624103c819087cb35a71c5868b6 |
completed | May 11, 2026, 12:05 p.m. |
| PDg | Predicate description generation | batch_6a01c749c7148190ad49ede859c60b75 |
completed | May 11, 2026, 12:10 p.m. |
Created at: April 30, 2026, 9:40 p.m.