Triple
T9813622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Příbor |
E238340
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Bieruń
Bieruń is a small town in southern Poland known for its historic architecture, coal-mining heritage, and location within the Silesian Voivodeship.
|
E823285
|
NE FINISHED |
How this triple was built (4 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: Bieruń | Statement: [Příbor, hasTwinTown, Bieruń]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bieruń Context triple: [Příbor, hasTwinTown, Bieruń]
-
A.
Gubałówka
Gubałówka is a popular hill and tourist destination in the Polish Tatra region, known for its panoramic views of Zakopane and the surrounding mountains.
-
B.
Bodzentyn
Bodzentyn is a small historic town in south-central Poland, known for its medieval ruins and scenic location in the Świętokrzyskie region.
-
C.
Brzeszcze
Brzeszcze is a small town in southern Poland, known in part as the longtime home of former Polish Prime Minister Beata Szydło.
-
D.
Brzesko
Brzesko is a town in southern Poland known for its historical architecture and regional brewing traditions.
-
E.
Koprzywnica
Koprzywnica is a small town in southeastern Poland known for its historic Cistercian monastery and location within the Świętokrzyskie Voivodeship.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bieruń Triple: [Příbor, hasTwinTown, Bieruń]
Generated description
Bieruń is a small town in southern Poland known for its historic architecture, coal-mining heritage, and location within the Silesian Voivodeship.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bieruń Target entity description: Bieruń is a small town in southern Poland known for its historic architecture, coal-mining heritage, and location within the Silesian Voivodeship.
-
A.
Gubałówka
Gubałówka is a popular hill and tourist destination in the Polish Tatra region, known for its panoramic views of Zakopane and the surrounding mountains.
-
B.
Bodzentyn
Bodzentyn is a small historic town in south-central Poland, known for its medieval ruins and scenic location in the Świętokrzyskie region.
-
C.
Brzeszcze
Brzeszcze is a small town in southern Poland, known in part as the longtime home of former Polish Prime Minister Beata Szydło.
-
D.
Brzesko
Brzesko is a town in southern Poland known for its historical architecture and regional brewing traditions.
-
E.
Koprzywnica
Koprzywnica is a small town in southeastern Poland known for its historic Cistercian monastery and location within the Świętokrzyskie Voivodeship.
- F. None of above. chosen
Provenance (5 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_69ca84defac48190abc1148804f184c1 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb22410208190b82b81a4df800f80 |
completed | April 2, 2026, 12:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc63c450819091e57030a48e7d88 |
completed | April 5, 2026, 2:43 a.m. |
| NEDg | Description generation | batch_69d1cce3d9d481909eaf7278dfe20955 |
completed | April 5, 2026, 2:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1cd5d1670819085c58ff8889318af |
completed | April 5, 2026, 2:47 a.m. |
Created at: March 30, 2026, 8:30 p.m.