Triple
T7540315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Timișoara |
E178257
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Temesvar |
E408997
|
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: Temesvar | Statement: [Timișoara, alternativeName, Temesvar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Temesvar Context triple: [Timișoara, alternativeName, Temesvar]
-
A.
Kolozsvár
Kolozsvár, known today as Cluj-Napoca, is a major historical and cultural city in Transylvania, Romania, with a significant Hungarian heritage.
-
B.
Temesvár
chosen
Temesvár is the historical name for Timișoara, a major city in western Romania that served as an important military and administrative center in the Habsburg Monarchy.
-
C.
Subotica
Subotica is a historic city in northern Serbia known for its Art Nouveau architecture and cultural diversity, located near the Hungarian border.
-
D.
Budavár
Budavár is the historic Buda Castle quarter of Budapest, known for its medieval streets, royal palace complex, and panoramic views over the Danube.
-
E.
Veszprém
Veszprém is a historic city in western Hungary known for its medieval castle district and role as a regional cultural 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_69c69f2be3888190a6667a27f8f195e9 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f873b17081908bb70aea0010d072 |
completed | March 27, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8be148dc881909f15e6457f11c775 |
completed | March 29, 2026, 5:52 a.m. |
Created at: March 27, 2026, 3:48 p.m.