Triple
T13022125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Provins |
E326197
|
entity |
| Predicate | mayor |
P185
|
FINISHED |
| Object |
Olivier Lavenka
Olivier Lavenka is a French politician who serves as the mayor of the historic town of Provins in the Île-de-France region.
|
E1014828
|
NE FINISHED |
How this triple was built (4 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: Olivier Lavenka | Statement: [Provins, mayor, Olivier Lavenka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Olivier Lavenka Context triple: [Provins, mayor, Olivier Lavenka]
-
A.
Mischa Bakaleinikoff
Mischa Bakaleinikoff was a Russian-born American film composer and musical director best known for his work on numerous Columbia Pictures productions in the mid-20th century.
-
B.
Sacha Pitoëff
Sacha Pitoëff was a French actor and theatre director known for his distinctive, often enigmatic screen presence in mid-20th-century European cinema.
-
C.
Pavel Lungin
Pavel Lungin is a Russian film director and screenwriter best known internationally for his award-winning films such as "Taxi Blues" and "The Island."
-
D.
Wenceslas Ferrand
Wenceslas Ferrand is an individual notable enough to be recognized as a prominent bearer of the surname Ferrand.
-
E.
Ustinov
Ustinov is a Russian surname most famously associated with Soviet military and political leader Dmitry Ustinov.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Olivier Lavenka Triple: [Provins, mayor, Olivier Lavenka]
Generated description
Olivier Lavenka is a French politician who serves as the mayor of the historic town of Provins in the Île-de-France region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Olivier Lavenka Target entity description: Olivier Lavenka is a French politician who serves as the mayor of the historic town of Provins in the Île-de-France region.
-
A.
Mischa Bakaleinikoff
Mischa Bakaleinikoff was a Russian-born American film composer and musical director best known for his work on numerous Columbia Pictures productions in the mid-20th century.
-
B.
Sacha Pitoëff
Sacha Pitoëff was a French actor and theatre director known for his distinctive, often enigmatic screen presence in mid-20th-century European cinema.
-
C.
Pavel Lungin
Pavel Lungin is a Russian film director and screenwriter best known internationally for his award-winning films such as "Taxi Blues" and "The Island."
-
D.
Wenceslas Ferrand
Wenceslas Ferrand is an individual notable enough to be recognized as a prominent bearer of the surname Ferrand.
-
E.
Ustinov
Ustinov is a Russian surname most famously associated with Soviet military and political leader Dmitry Ustinov.
- F. None of above. chosen
Provenance (5 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_69d8076cc45c81908123123f43e69266 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97ed05e9c8190a4f208662bca0602 |
completed | April 10, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c119e19c81908ae2b1caff6f2f32 |
completed | May 3, 2026, 3:29 a.m. |
| NEDg | Description generation | batch_69f6c20aff008190a1a10ac02ed08726 |
completed | May 3, 2026, 3:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6c2de143c81908164f5df2b92e5c3 |
completed | May 3, 2026, 3:37 a.m. |
Created at: April 9, 2026, 8:52 p.m.