Triple
T10985641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elena Ivanovna Diakonova |
E259621
|
entity |
| Predicate | burialPlace |
P196
|
FINISHED |
| Object | Púbol |
E223584
|
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: Púbol | Statement: [Elena Ivanovna Diakonova, burialPlace, Púbol]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Púbol Context triple: [Elena Ivanovna Diakonova, burialPlace, Púbol]
-
A.
Púbol
chosen
Púbol is a small village in Catalonia, Spain, best known for the castle that Salvador Dalí bought and transformed for his wife Gala, now a major part of the Dalí museum triangle.
-
B.
Paible
Paible is a small coastal settlement on the island of North Uist in Scotland’s Outer Hebrides.
-
C.
Bobadela
Bobadela is a suburban locality in the Lisbon metropolitan area of Portugal, known primarily as a residential and industrial zone near the Tagus River.
-
D.
Pereire
Pereire is a Paris Métro station in the 17th arrondissement, serving as a stop on Line 3 and connecting to nearby RER services.
-
E.
Fiquet
Fiquet is a French surname most notably borne by Hortense Fiquet, the model and wife of painter Paul Cézanne.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d787b2e4a88190a81504eee77e2298 |
completed | April 9, 2026, 11:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e344e9c66c81909163cea6aa9276e0 |
completed | April 18, 2026, 8:46 a.m. |
Created at: April 8, 2026, 9:24 p.m.