Triple
T13435329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Baltimore Aquatic Club |
E320214
|
entity |
| Predicate | notableAthlete |
P10392
|
FINISHED |
| Object |
Yannick Agnel
Yannick Agnel is a French Olympic and world champion freestyle swimmer known for his dominance in middle-distance events, particularly at the 2012 London Games.
|
E1050909
|
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: Yannick Agnel | Statement: [North Baltimore Aquatic Club, notableAthlete, Yannick Agnel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yannick Agnel Context triple: [North Baltimore Aquatic Club, notableAthlete, Yannick Agnel]
-
A.
Arnaud Péricard
Arnaud Péricard is a French politician and lawyer known for serving as the mayor of the affluent Parisian suburb of Saint-Germain-en-Laye.
-
B.
Fabrice Lecomte
Fabrice Lecomte is a composer and musician best known for creating the musical score for the romantic drama film "Sylvie’s Love."
-
C.
Jean Pascal
Jean Pascal is a Haitian-Canadian professional boxer and former light heavyweight world champion known for his explosive style and high-profile title fights.
-
D.
Didier Hoarau
Didier Hoarau is a film producer known for his work on the action thriller movie "Taken."
-
E.
Stéphane Roche
Stéphane Roche is an editor known for his work on the publication "The Voices."
- 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: Yannick Agnel Triple: [North Baltimore Aquatic Club, notableAthlete, Yannick Agnel]
Generated description
Yannick Agnel is a French Olympic and world champion freestyle swimmer known for his dominance in middle-distance events, particularly at the 2012 London Games.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yannick Agnel Target entity description: Yannick Agnel is a French Olympic and world champion freestyle swimmer known for his dominance in middle-distance events, particularly at the 2012 London Games.
-
A.
Arnaud Péricard
Arnaud Péricard is a French politician and lawyer known for serving as the mayor of the affluent Parisian suburb of Saint-Germain-en-Laye.
-
B.
Fabrice Lecomte
Fabrice Lecomte is a composer and musician best known for creating the musical score for the romantic drama film "Sylvie’s Love."
-
C.
Jean Pascal
Jean Pascal is a Haitian-Canadian professional boxer and former light heavyweight world champion known for his explosive style and high-profile title fights.
-
D.
Didier Hoarau
Didier Hoarau is a film producer known for his work on the action thriller movie "Taken."
-
E.
Stéphane Roche
Stéphane Roche is an editor known for his work on the publication "The Voices."
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaee29fec81908b07b4fca2922242 |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f77f7dcb8481909299419234dd30fe |
completed | May 3, 2026, 5:01 p.m. |
| NEDg | Description generation | batch_69f78043e4dc8190a996cc14d1ba6d0b |
completed | May 3, 2026, 5:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f780d1a4c48190afc8060c6e065e00 |
completed | May 3, 2026, 5:07 p.m. |
Created at: April 9, 2026, 9:40 p.m.