Triple
T502598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern France |
E10430
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Besançon |
E64224
|
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: Besançon | Statement: [Eastern France, containsCity, Besançon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Besançon Context triple: [Eastern France, containsCity, Besançon]
-
A.
Besançon
chosen
Besançon is a historic city in eastern France, known for its well-preserved Vauban fortifications, rich cultural heritage, and role as a regional administrative and educational center.
-
B.
Bourg-en-Bresse
Bourg-en-Bresse is a historic town in eastern France known as the capital of the Ain department, noted for its Renaissance architecture and the royal monastery of Brou.
-
C.
Mulhouse
Mulhouse is an industrial city in northeastern France near the Swiss and German borders, known for its textile heritage and major technical museums.
-
D.
Dijon
Dijon is a historic city in eastern France renowned for its rich architectural heritage, former status as the capital of the Duchy of Burgundy, and its famous mustard.
-
E.
Strasbourg
Strasbourg is a major French city on the Rhine known for hosting key European institutions, including the European Parliament and the Council of Europe.
- 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_69a2e848adf881908e5e04f7af030093 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1339748819089f89691a1698dd9 |
completed | Feb. 28, 2026, 1:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7b830bf5c81908784e8146987eb96 |
completed | March 4, 2026, 4:42 a.m. |
Created at: Feb. 28, 2026, 1:12 p.m.