Triple
T5743571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cible émouvante |
E126673
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Philippe Martin
Philippe Martin is a French film producer known for his work on acclaimed European cinema.
|
E636915
|
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: Philippe Martin | Statement: [Cible émouvante, producer, Philippe Martin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Philippe Martin Context triple: [Cible émouvante, producer, Philippe Martin]
-
A.
Philippe Denis
Philippe Denis is a cinematographer best known for his work on the animated film "Megamind."
-
B.
Stéphane Préfontaine
Stéphane Préfontaine is a Canadian former middle-distance runner best known for serving as one of the final torchbearers who lit the Olympic cauldron at the 1976 Montreal Summer Olympics.
-
C.
Stéphane Loda
Stéphane Loda is a French local politician who serves as the mayor of the Mediterranean coastal commune of Canet-en-Roussillon.
-
D.
Jean-Philippe Lauer
Jean-Philippe Lauer was a French archaeologist best known for his decades-long work restoring and studying the Step Pyramid complex of Djoser at Saqqara in Egypt.
-
E.
Philippe Martinaud
Philippe Martinaud is a lighting designer known for creating the illumination scheme of Tbilisi’s iconic Bridge of Peace.
- 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: Philippe Martin Triple: [Cible émouvante, producer, Philippe Martin]
Generated description
Philippe Martin is a French film producer known for his work on acclaimed European cinema.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Philippe Martin Target entity description: Philippe Martin is a French film producer known for his work on acclaimed European cinema.
-
A.
Philippe Denis
Philippe Denis is a cinematographer best known for his work on the animated film "Megamind."
-
B.
Stéphane Préfontaine
Stéphane Préfontaine is a Canadian former middle-distance runner best known for serving as one of the final torchbearers who lit the Olympic cauldron at the 1976 Montreal Summer Olympics.
-
C.
Stéphane Loda
Stéphane Loda is a French local politician who serves as the mayor of the Mediterranean coastal commune of Canet-en-Roussillon.
-
D.
Jean-Philippe Lauer
Jean-Philippe Lauer was a French archaeologist best known for his decades-long work restoring and studying the Step Pyramid complex of Djoser at Saqqara in Egypt.
-
E.
Philippe Martinaud
Philippe Martinaud is a lighting designer known for creating the illumination scheme of Tbilisi’s iconic Bridge of Peace.
- 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_69c0083179548190b384b0bf3c08ca4d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02586b25c819083c409ce324268cc |
completed | March 22, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c775058c388190bba04cff5dba997a |
completed | March 28, 2026, 6:28 a.m. |
| NEDg | Description generation | batch_69c776cee4b08190ae2ba38a0155a3b4 |
completed | March 28, 2026, 6:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7777f16e08190804af2c35659d498 |
completed | March 28, 2026, 6:38 a.m. |
Created at: March 22, 2026, 3:48 p.m.