Triple
T5574151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chełm mountain |
E146276
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Myślenice |
E26049
|
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: Myślenice | Statement: [Chełm mountain, locatedNear, Myślenice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Myślenice Context triple: [Chełm mountain, locatedNear, Myślenice]
-
A.
Myślenice
chosen
Myślenice is a historic town in southern Poland known for its picturesque setting near the Carpathian foothills and its role as a local cultural and tourist center.
-
B.
Mołodeczno
Mołodeczno is a town in present-day Belarus that historically served as an important regional center in the former Wilno Voivodeship.
-
C.
Działdowo
Działdowo is a town in northern Poland known for its historical significance and location within the Warmian-Masurian Voivodeship.
-
D.
Oleśnica
Oleśnica is a historic town in southwestern Poland known for its Renaissance castle and well-preserved old town.
-
E.
Krzeszowice
Krzeszowice is a town in southern Poland known for its historic spa traditions and picturesque location near Kraków.
- 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_69c008ffed108190a084602227af6157 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c02054ce8c819093e1a6379ec92006 |
completed | March 22, 2026, 5:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c02852a6fc8190a543508ab3237f95 |
completed | March 22, 2026, 5:35 p.m. |
Created at: March 22, 2026, 3:37 p.m.