Triple
T8072229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Picasso family |
E188400
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Vallauris |
E56112
|
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: Vallauris | Statement: [Picasso family, associatedWith, Vallauris]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vallauris Context triple: [Picasso family, associatedWith, Vallauris]
-
A.
Vallauris
chosen
Vallauris is a town in the French Riviera renowned for its pottery tradition and its association with Pablo Picasso, who lived and worked there for several years.
-
B.
Éveux
Éveux is a small commune in eastern France’s Rhône department, known for hosting Le Corbusier’s modernist monastery, the Couvent Sainte-Marie de La Tourette.
-
C.
Vauvert
Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
-
D.
Vogogna
Vogogna is a small historic village in northern Italy’s Piedmont region, known for its medieval castle and well-preserved old town within the Ossola Valley.
-
E.
Vaujours
Vaujours is a small suburban commune in the northeastern outskirts of Paris, France.
- 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_69ca82b50c708190863f661d438e68df |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb40482200819086c639f64c01fbb5 |
completed | March 31, 2026, 3:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cceceb7fa48190b1013a25fd8f14a5 |
completed | April 1, 2026, 10:01 a.m. |
Created at: March 30, 2026, 5:27 p.m.