Triple
T7071026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gorce Mountains |
E164694
|
entity |
| Predicate | nearestCity |
P350
|
FINISHED |
| Object | Limanowa |
E307610
|
NE 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: Limanowa | Statement: [Gorce Mountains, nearestCity, Limanowa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Limanowa Context triple: [Gorce Mountains, nearestCity, Limanowa]
-
A.
Limanowa
chosen
Limanowa is a small town in southern Poland, located in the Lesser Poland Voivodeship, known for its historical significance and picturesque mountainous surroundings.
-
B.
Ustka
Ustka is a Baltic Sea coastal town in northern Poland known as a popular seaside resort and fishing port.
-
C.
Kwidzyn
Kwidzyn is a historic town in northern Poland known for its medieval Teutonic castle complex and Gothic cathedral.
-
D.
Elbląg
Elbląg is a historic city in northern Poland known for its reconstructed Old Town, medieval heritage, and role as an important port and industrial center.
-
E.
Kościerzyna
Kościerzyna is a historic town in northern Poland known as a local cultural and economic center within the Kashubian region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c6887b96548190a8a9b3ac8adf4119 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4c862f481908d1faf6ed57774f1 |
completed | March 27, 2026, 8:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7d372ca248190bd5aa6b1648199f2 |
completed | March 28, 2026, 1:11 p.m. |
Created at: March 27, 2026, 2:39 p.m.