Triple
T457924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French–Luxembourg border |
E7272
|
entity |
| Predicate | hasNearbyCity |
P350
|
FINISHED |
| Object | Thionville |
E58199
|
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: Thionville | Statement: [French–Luxembourg border, hasNearbyCity, Thionville]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thionville Context triple: [French–Luxembourg border, hasNearbyCity, Thionville]
-
A.
Thionville
chosen
Thionville is a town in northeastern France near the Luxembourg border, known historically as a strategic industrial and military center in the Moselle region.
-
B.
Mulhouse
Mulhouse is an industrial city in northeastern France near the Swiss and German borders, known for its textile heritage and major technical museums.
-
C.
Besançon
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.
-
D.
Mondorf-les-Bains
Mondorf-les-Bains is a spa town in southeastern Luxembourg renowned for its thermal baths, wellness facilities, and casino.
-
E.
Colmar
Colmar is a picturesque historic town in northeastern France’s Alsace region, renowned for its well-preserved medieval and early Renaissance architecture and canals.
- 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efa3163081909acff040a22bd559 |
completed | Feb. 28, 2026, 1:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a6373fbf388190afb01fcfd67f03bf |
completed | March 3, 2026, 1:19 a.m. |
Created at: Feb. 28, 2026, 1:12 p.m.