Triple
T12134489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hanau |
E289017
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Jarosław |
E284545
|
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: Jarosław | Statement: [Hanau, twinTown, Jarosław]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jarosław Context triple: [Hanau, twinTown, Jarosław]
-
A.
Jarosław
chosen
Jarosław is a historic town in southeastern Poland known for its well-preserved Old Town and role as a former important trade center.
-
B.
Jasło
Jasło is a small town in southeastern Poland, known as part of the historical region of Galicia and for its cultural and educational traditions.
-
C.
Hrubieszów
Hrubieszów is a historic town in eastern Poland near the Ukrainian border, known for its multicultural heritage and location in the Lublin region.
-
D.
Kalisz
Kalisz is one of Poland’s oldest cities, located in the Greater Poland region and known for its historical architecture and cultural heritage.
-
E.
Ostrołęka
Ostrołęka is a town in east-central Poland known for its historical role in the Napoleonic Wars and as a local industrial and administrative center.
- 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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9158c59e0819094d4522a107482b2 |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f68c8ee081908a0331805f62cb0d |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 8, 2026, 9:49 p.m.