Triple
T20735549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pierre Lescure |
E509692
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Lescure
Lescure is a French surname most notably borne by Pierre Lescure, a prominent media executive and former head of the Cannes Film Festival.
|
E1503810
|
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: Lescure | Statement: [Pierre Lescure, familyName, Lescure]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lescure Context triple: [Pierre Lescure, familyName, Lescure]
-
A.
Mourenx
Mourenx is a commune in southwestern France’s Pyrénées-Atlantiques department, developed in the mid-20th century as a planned industrial town linked to nearby natural gas fields.
-
B.
Bellecourt
Bellecourt is a surname most notably associated with Native American activist Vernon Bellecourt.
-
C.
Serques
Serques is a small commune in the Pas-de-Calais department in northern France, situated within the administrative area of Saint-Omer.
-
D.
Assencières
Assencières is a small commune in the Aube department of north-central France.
-
E.
Montfavet
Montfavet is a district of Avignon in southeastern France, known in part for its psychiatric hospital where sculptor Camille Claudel spent her final years and died.
- 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: Lescure Triple: [Pierre Lescure, familyName, Lescure]
Generated description
Lescure is a French surname most notably borne by Pierre Lescure, a prominent media executive and former head of the Cannes Film Festival.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lescure Target entity description: Lescure is a French surname most notably borne by Pierre Lescure, a prominent media executive and former head of the Cannes Film Festival.
-
A.
Mourenx
Mourenx is a commune in southwestern France’s Pyrénées-Atlantiques department, developed in the mid-20th century as a planned industrial town linked to nearby natural gas fields.
-
B.
Bellecourt
Bellecourt is a surname most notably associated with Native American activist Vernon Bellecourt.
-
C.
Serques
Serques is a small commune in the Pas-de-Calais department in northern France, situated within the administrative area of Saint-Omer.
-
D.
Assencières
Assencières is a small commune in the Aube department of north-central France.
-
E.
Montfavet
Montfavet is a district of Avignon in southeastern France, known in part for its psychiatric hospital where sculptor Camille Claudel spent her final years and died.
- 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_69e0b4c589c08190834fb5d86d0efa2b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c20a02d48190bba22d1bdbeb370d |
completed | April 21, 2026, 12:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a45c718208190939b58a14d5ab366 |
completed | May 17, 2026, 10:48 p.m. |
| NEDg | Description generation | batch_6a0a47375518819091234278dfc326eb |
completed | May 17, 2026, 10:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a47a51cb88190856282fdfa56460b |
completed | May 17, 2026, 10:56 p.m. |
Created at: April 16, 2026, 12:31 p.m.