Triple
T9251418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orzysz |
E222331
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Pisz |
E220534
|
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: Pisz | Statement: [Orzysz, near, Pisz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pisz Context triple: [Orzysz, near, Pisz]
-
A.
Pisz
chosen
Pisz is a town in northeastern Poland known for its location in the Masurian Lake District and proximity to extensive forests and lakes.
-
B.
Spisz
Spisz is a historical and ethnographic region in southern Poland and northern Slovakia, known for its mountainous landscapes, traditional highlander culture, and well-preserved medieval towns.
-
C.
Pyrzyce
Pyrzyce is a historic town in northwestern Poland known for its medieval fortifications and location within the West Pomeranian region.
-
D.
Piecki
Piecki is a village in northern Poland located in the Warmian-Masurian Voivodeship, known for its proximity to the region’s lakes and forests.
-
E.
Witos
Witos is a Polish surname most notably borne by Wincenty Witos, a prominent early 20th-century Polish politician and three-time Prime Minister.
- 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_69ca841d2b18819089f9faf5b2c2aec0 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd05f9ade48190ac8425a1c6f066b1 |
completed | April 1, 2026, 11:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0780650648190bc85452678268134 |
completed | April 4, 2026, 2:31 a.m. |
Created at: March 30, 2026, 7:31 p.m.