Triple
T17375197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Collège Sévigné |
E422417
|
entity |
| Predicate | hasAlumnus |
P51
|
FINISHED |
| Object |
Suzanne Lacore
Suzanne Lacore was a French socialist politician, feminist, and educator who became one of the first female undersecretaries of state in France’s Popular Front government in the 1930s.
|
E1267176
|
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: Suzanne Lacore | Statement: [Collège Sévigné, hasAlumnus, Suzanne Lacore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suzanne Lacore Context triple: [Collège Sévigné, hasAlumnus, Suzanne Lacore]
-
A.
Suzanne Pettit
Suzanne Pettit is an editor known for her work on the publication "Testament."
-
B.
Suzanne Barbieri
Suzanne Barbieri is a musician best known for her past role in the British progressive rock band Porcupine Tree.
-
C.
Donna Rancourt
Donna Rancourt is known as one of the former wives of American actor Ernest Borgnine.
-
D.
Suzanne Bourgeois
Suzanne Bourgeois is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Bourgeois.
-
E.
Julie LeBreton
Julie LeBreton is a Canadian actress known for her work in film and television, particularly in French-language productions.
- 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: Suzanne Lacore Triple: [Collège Sévigné, hasAlumnus, Suzanne Lacore]
Generated description
Suzanne Lacore was a French socialist politician, feminist, and educator who became one of the first female undersecretaries of state in France’s Popular Front government in the 1930s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Suzanne Lacore Target entity description: Suzanne Lacore was a French socialist politician, feminist, and educator who became one of the first female undersecretaries of state in France’s Popular Front government in the 1930s.
-
A.
Suzanne Pettit
Suzanne Pettit is an editor known for her work on the publication "Testament."
-
B.
Suzanne Barbieri
Suzanne Barbieri is a musician best known for her past role in the British progressive rock band Porcupine Tree.
-
C.
Donna Rancourt
Donna Rancourt is known as one of the former wives of American actor Ernest Borgnine.
-
D.
Suzanne Bourgeois
Suzanne Bourgeois is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Bourgeois.
-
E.
Julie LeBreton
Julie LeBreton is a Canadian actress known for her work in film and television, particularly in French-language productions.
- 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_69d889d6535c81908be333c01deaec4e |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a6c864481908507290282cc6d25 |
completed | April 19, 2026, 2:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01a7ed9e988190a60106a1a0f94210 |
completed | May 11, 2026, 9:57 a.m. |
| NEDg | Description generation | batch_6a01a886818881909f237f69c6d77f93 |
completed | May 11, 2026, 9:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01a9183410819083c8239e3ce38ea2 |
completed | May 11, 2026, 10:02 a.m. |
Created at: April 10, 2026, 5:44 a.m.