Triple
T2930680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nancy |
E78951
|
entity |
| Predicate | hasMayor |
P185
|
FINISHED |
| Object |
Mathieu Klein
Mathieu Klein is a French politician known for serving as the mayor of the city of Nancy.
|
E312926
|
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: Mathieu Klein | Statement: [Nancy, hasMayor, Mathieu Klein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mathieu Klein Context triple: [Nancy, hasMayor, Mathieu Klein]
-
A.
Julien Flegenheimer
Julien Flegenheimer was an architect best known for his role in designing the Palais des Nations, the former League of Nations headquarters in Geneva.
-
B.
Fabien Roussel
Fabien Roussel is a French politician who has served as the national secretary and presidential candidate of the French Communist Party.
-
C.
Julien BriseBois
Julien BriseBois is a Canadian ice hockey executive best known for building and leading the Tampa Bay Lightning into a modern NHL powerhouse and multiple-time Stanley Cup champion.
-
D.
Laurent Lomet
Laurent Lomet was a mountaineer known for participating in the first recorded ascent of Monte Perdido in the Pyrenees.
-
E.
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.
- 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: Mathieu Klein Triple: [Nancy, hasMayor, Mathieu Klein]
Generated description
Mathieu Klein is a French politician known for serving as the mayor of the city of Nancy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mathieu Klein Target entity description: Mathieu Klein is a French politician known for serving as the mayor of the city of Nancy.
-
A.
Julien Flegenheimer
Julien Flegenheimer was an architect best known for his role in designing the Palais des Nations, the former League of Nations headquarters in Geneva.
-
B.
Fabien Roussel
Fabien Roussel is a French politician who has served as the national secretary and presidential candidate of the French Communist Party.
-
C.
Julien BriseBois
Julien BriseBois is a Canadian ice hockey executive best known for building and leading the Tampa Bay Lightning into a modern NHL powerhouse and multiple-time Stanley Cup champion.
-
D.
Laurent Lomet
Laurent Lomet was a mountaineer known for participating in the first recorded ascent of Monte Perdido in the Pyrenees.
-
E.
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.
- 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_69ad8b0d40b481908bc2a5fa2e73c3fb |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad980191388190ac2455a7d9867be3 |
completed | March 8, 2026, 3:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b086703868819083eacc3fe392fde1 |
completed | March 10, 2026, 9 p.m. |
| NEDg | Description generation | batch_69b0d21ad8908190bf232b48d8766f59 |
completed | March 11, 2026, 2:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b0d278538481909f573d77cb0338da |
completed | March 11, 2026, 2:24 a.m. |
Created at: March 8, 2026, 2:55 p.m.