Triple
T11130779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Troisvierges |
E263272
|
entity |
| Predicate | hasLocality |
P7943
|
FINISHED |
| Object | Troisvierges (town) |
E263272
|
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: Troisvierges (town) | Statement: [Troisvierges, hasLocality, Troisvierges (town)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Troisvierges (town) Context triple: [Troisvierges, hasLocality, Troisvierges (town)]
-
A.
Trévières
Trévières is a commune in the Calvados department of Normandy in northwestern France, known for its proximity to the D-Day landing beaches and its World War II history.
-
B.
Troisvierges
chosen
Troisvierges is a small town and commune in northern Luxembourg known for its railway junction and proximity to the borders with Belgium and Germany.
-
C.
Verrières
Verrières is a small French commune located within the Thiers arrondissement in the Puy-de-Dôme department of central France.
-
D.
Souvigny
Souvigny is a historic town in central France known for its important Cluniac priory and medieval religious heritage.
-
E.
Saint-Paul-Trois-Châteaux
Saint-Paul-Trois-Châteaux is a historic commune in southeastern France known for its medieval architecture and Romanesque cathedral.
- 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e831f4808190afabdaa0e97bbe32 |
completed | April 9, 2026, 5:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e441dcb4608190a4cfa46c194d11ae |
completed | April 19, 2026, 2:45 a.m. |
Created at: April 8, 2026, 9:28 p.m.