Triple
T10217200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Picardy |
E242475
|
entity |
| Predicate | hasHistoricalProvince |
P5057
|
FINISHED |
| Object | Vimeu |
E460549
|
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: Vimeu | Statement: [Picardy, hasHistoricalProvince, Vimeu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vimeu Context triple: [Picardy, hasHistoricalProvince, Vimeu]
-
A.
Vimeu
chosen
Vimeu is a historical region in northern France, known for its medieval significance and as the site of the Battle of Saucourt-en-Vimeu.
-
B.
Viacha
Viacha is a Bolivian city in the Altiplano region known for its industrial activity and proximity to La Paz.
-
C.
Vimioso
Vimioso is a municipality in northeastern Portugal known for its strong cultural ties to the Mirandese language and traditional rural heritage.
-
D.
Vilca
Vilca is a small Andean town in Peru known for its scenic highland landscapes, lagoons, and traditional rural culture within the Nor Yauyos-Cochas reserve.
-
E.
Mvezo
Mvezo is a small rural village in South Africa’s Eastern Cape best known as the birthplace of Nelson Mandela.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa6e544c8190961cdd7f1fbe24e6 |
completed | April 6, 2026, 12:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6a8142f948190b19e3c1f70f6430f |
completed | April 8, 2026, 7:10 p.m. |
Created at: April 6, 2026, 11:06 a.m.