Triple
T10705644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nanterre |
E252395
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Zilina |
E218081
|
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: Zilina | Statement: [Nanterre, hasTwinTown, Zilina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zilina Context triple: [Nanterre, hasTwinTown, Zilina]
-
A.
Karviná
Karviná is an industrial city in the Moravian-Silesian Region of the Czech Republic, historically part of Cieszyn Silesia and known for its coal mining heritage.
-
B.
Lučenec
Lučenec is a town in southern Slovakia known as a regional center of trade, transport, and culture in the Novohrad area.
-
C.
Zlín
Zlín is a city in the Czech Republic known for its modernist architecture and historical association with the Baťa shoe company.
-
D.
Opava
Opava is a historic city in the Czech Republic’s Silesian region, known as a former political and cultural center of Silesia.
-
E.
Žilina
chosen
Žilina is a city in northwestern Slovakia that serves as an important industrial and transportation hub, particularly for rail connections in the region.
- 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_69d6aa5cbabc8190973e683950d89faf |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fddeb060819094cd125a68070eb2 |
completed | April 9, 2026, 1:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f489b62b808190a3fc89e73e8ae2f7 |
completed | May 1, 2026, 11:08 a.m. |
Created at: April 8, 2026, 9:12 p.m.