Triple
T13826574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Polkowice |
E332265
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Lubin |
—
|
NE NERFINISHED |
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: Lubin | Statement: [Polkowice, nearbyCity, Lubin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lubin Context triple: [Polkowice, nearbyCity, Lubin]
-
A.
Lubin
chosen
Lubin is a town in southwestern Poland known for its copper mining industry and location within the Lower Silesian region.
-
B.
Lubawa
Lubawa is a historic town in northern Poland known for its medieval heritage and location within the Warmian-Masurian region.
-
C.
Olsztynek
Olsztynek is a small historic town in northern Poland known for its open-air ethnographic museum and location within the picturesque Warmian-Masurian lake district.
-
D.
Wolsztyn
Wolsztyn is a town in western Poland known for its historic steam locomotive depot and annual steam engine parade.
-
E.
Lublin
Lublin is a historic city in eastern Poland known as a major cultural, academic, and economic center and for its significant role in Polish political history.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d81c5ae7c88190b0dd41bdafeb5999 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0295d2d48190b08eba0d805bd72d |
completed | April 14, 2026, 9:02 a.m. |
Created at: April 9, 2026, 10:13 p.m.