Triple
T15619764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Issy-les-Moulineaux |
E375517
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Frameries |
E407910
|
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: Frameries | Statement: [Issy-les-Moulineaux, hasTwinTown, Frameries]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frameries Context triple: [Issy-les-Moulineaux, hasTwinTown, Frameries]
-
A.
Frameries
chosen
Frameries is a municipality in the province of Hainaut in Wallonia, Belgium, known historically for its coal mining and as part of the Borinage industrial region.
-
B.
Feigères
Feigères is a small French commune in the Haute-Savoie department in the Auvergne-Rhône-Alpes region of southeastern France.
-
C.
Fräschels
Fräschels is a small municipality in the canton of Fribourg in western Switzerland, situated near the linguistic border between German- and French-speaking regions.
-
D.
Floreffe
Floreffe is a municipality in Wallonia, Belgium, known for its historic abbey and location along the Sambre River in Namur Province.
-
E.
Fonds-Verrettes
Fonds-Verrettes is a mountainous commune in southeastern Haiti near the Dominican border, known for its rural character and vulnerability to flooding and landslides.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e997ce481909b2f10d25705fbc6 |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff5f3b643c819093230df6cfe440b9 |
completed | May 9, 2026, 4:22 p.m. |
Created at: April 10, 2026, 4:13 a.m.