Triple
T20655598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reutlingen |
E507617
|
entity |
| Predicate | twinCity |
P1072
|
FINISHED |
| Object | Roanne |
—
|
NE NERFINISHED |
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: Roanne | Statement: [Reutlingen, twinCity, Roanne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roanne Context triple: [Reutlingen, twinCity, Roanne]
-
A.
Roanne
chosen
Roanne is a commune and industrial town in central France, situated on the Loire River and known historically for its textile industry and river port.
-
B.
Tournus
Tournus is a historic town in eastern France’s Burgundy region, known for its Romanesque abbey and riverside setting along the Saône.
-
C.
Bressuire
Bressuire is a historic town in western France known for its medieval castle and role as an administrative center in the Deux-Sèvres department.
-
D.
Bourgueil
Bourgueil is a Loire Valley wine appellation in France renowned for its red wines, particularly those made predominantly from Cabernet Franc.
-
E.
Bourg
Bourg is a metro station on the Lille Metro network in northern France, serving local passengers on Line 2.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4bf58c081908e52a4500e03ff83 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b2ed48308190b9350a323b9a7952 |
completed | April 20, 2026, 11:12 p.m. |
Created at: April 16, 2026, 11:43 a.m.