Triple
T8320591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orléans |
E194820
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Lugoj |
E291973
|
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: Lugoj | Statement: [Orléans, hasTwinTown, Lugoj]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lugoj Context triple: [Orléans, hasTwinTown, Lugoj]
-
A.
Lugoj
chosen
Lugoj is a town in western Romania, situated on the Timiș River, known for its historical architecture and cultural heritage in the Banat region.
-
B.
Diass
Diass is a commune in western Senegal that hosts the country’s main international gateway, Blaise Diagne International Airport.
-
C.
Lugos
Lugos is a town in present-day Romania, historically part of the Austro-Hungarian Empire, known as the birthplace of actor Bela Lugosi.
-
D.
Sokal
Sokal is a small town in western Ukraine’s Lviv Oblast, historically part of Galicia and situated near the Bug River close to the Polish border.
-
E.
Lübars
Lübars is a historic, village-like district in Berlin’s Reinickendorf borough, known for its rural character, fields, and preserved traditional architecture within the city.
- 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_69ca82e7a8a88190a32bb5cc0feb012d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f6686a0819094abc2bfd2e500a5 |
completed | March 31, 2026, 8:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd95a058948190b056d9b0f0607933 |
completed | April 1, 2026, 10:01 p.m. |
Created at: March 30, 2026, 5:55 p.m.