Triple
T7280191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Breton |
E163126
|
entity |
| Predicate | notableBearersInclude |
P2531
|
FINISHED |
| Object |
Philippe Le Breton
Philippe Le Breton is a French individual known primarily as a notable bearer of the surname Le Breton.
|
E849204
|
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 Le Breton | Statement: [Le Breton, notableBearersInclude, Philippe Le Breton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Philippe Le Breton Context triple: [Le Breton, notableBearersInclude, Philippe Le Breton]
-
A.
Frédéric Bricout
Frédéric Bricout is a French politician who serves as the mayor of the northern French city of Cambrai.
-
B.
Jean Le Breton
Jean Le Breton was a prominent French statesman and royal official of the early 16th century, best known for his role in the development of Renaissance châteaux in the Loire Valley.
-
C.
Philippe Forquet
Philippe Forquet was a French actor and 1960s heartthrob best known for his romantic lead roles in films that paired him with prominent international actresses.
-
D.
François Lecointre
François Lecointre is a French Army general who served as France’s Chief of the Defence Staff.
-
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 Le Breton Triple: [Le Breton, notableBearersInclude, Philippe Le Breton]
Generated description
Philippe Le Breton is a French individual known primarily as a notable bearer of the surname Le Breton.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Philippe Le Breton Target entity description: Philippe Le Breton is a French individual known primarily as a notable bearer of the surname Le Breton.
-
A.
Frédéric Bricout
Frédéric Bricout is a French politician who serves as the mayor of the northern French city of Cambrai.
-
B.
Jean Le Breton
Jean Le Breton was a prominent French statesman and royal official of the early 16th century, best known for his role in the development of Renaissance châteaux in the Loire Valley.
-
C.
Philippe Forquet
Philippe Forquet was a French actor and 1960s heartthrob best known for his romantic lead roles in films that paired him with prominent international actresses.
-
D.
François Lecointre
François Lecointre is a French Army general who served as France’s Chief of the Defence Staff.
-
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_69c6885c5964819085b209701769877f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb339b1081909f648864e210f98e |
completed | March 27, 2026, 8:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d5e25dcb108190aaed79d8c64361a8 |
completed | April 8, 2026, 5:06 a.m. |
| NEDg | Description generation | batch_69d5e444bce081909ffb98def6d8acc3 |
completed | April 8, 2026, 5:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d5e5e817f481908a05f6968e973e2c |
completed | April 8, 2026, 5:21 a.m. |
Created at: March 27, 2026, 2:59 p.m.