Triple
T12455393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mapou Yanga-Mbiwa |
E297642
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Mapou
Mapou is a French former professional footballer best known for his role as a central defender for clubs such as Montpellier, Newcastle United, and AS Roma, as well as the French national team.
|
E983322
|
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: Mapou | Statement: [Mapou Yanga-Mbiwa, givenName, Mapou]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mapou Context triple: [Mapou Yanga-Mbiwa, givenName, Mapou]
-
A.
Delmas
Delmas is a densely populated suburban commune forming part of the Port-au-Prince metropolitan area in Haiti.
-
B.
Laporte
Laporte is a small borough that serves as the county seat of Sullivan County in northeastern Pennsylvania.
-
C.
Laporte
Laporte is a surname of French origin borne by various notable individuals across fields such as science, sports, and politics.
-
D.
DuBourg
DuBourg is a French-origin surname historically associated with notable figures in politics, religion, and public life.
-
E.
Grand Marais
Grand Marais is a small harbor town on Minnesota’s North Shore of Lake Superior, known for its scenic shoreline, outdoor recreation, and arts community.
- 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: Mapou Triple: [Mapou Yanga-Mbiwa, givenName, Mapou]
Generated description
Mapou is a French former professional footballer best known for his role as a central defender for clubs such as Montpellier, Newcastle United, and AS Roma, as well as the French national team.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mapou Target entity description: Mapou is a French former professional footballer best known for his role as a central defender for clubs such as Montpellier, Newcastle United, and AS Roma, as well as the French national team.
-
A.
Delmas
Delmas is a densely populated suburban commune forming part of the Port-au-Prince metropolitan area in Haiti.
-
B.
Laporte
Laporte is a small borough that serves as the county seat of Sullivan County in northeastern Pennsylvania.
-
C.
Laporte
Laporte is a surname of French origin borne by various notable individuals across fields such as science, sports, and politics.
-
D.
DuBourg
DuBourg is a French-origin surname historically associated with notable figures in politics, religion, and public life.
-
E.
Grand Marais
Grand Marais is a small harbor town on Minnesota’s North Shore of Lake Superior, known for its scenic shoreline, outdoor recreation, and arts community.
- 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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94da2a3cc81908de5a85257627fe2 |
completed | April 10, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63f190c788190adceaab8117d52a6 |
completed | May 2, 2026, 6:14 p.m. |
| NEDg | Description generation | batch_69f6405f9f6481909bcc3b2e3deeae7e |
completed | May 2, 2026, 6:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6416ba1bc8190a772bffe4d83ec15 |
completed | May 2, 2026, 6:24 p.m. |
Created at: April 8, 2026, 9:56 p.m.