Triple

T14896344
Position Surface form Disambiguated ID Type / Status
Subject FC Metz E359885 entity
Predicate nickName P2937 FINISHED
Object Le FCM
Le FCM is the common nickname of FC Metz, a French professional football club based in Metz, Lorraine.
 E1125091 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: Le FCM | Statement: [FC Metz, nickName, Le FCM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Le FCM
Context triple: [FC Metz, nickName, Le FCM]
  • A. Le DFCO
    Le DFCO is the commonly used nickname for Dijon FCO, a French professional football club based in Dijon.
  • B. Le MUC
    Le MUC is the commonly used nickname for the French football club Le Mans FC.
  • C. Fréquence Plus
    Fréquence Plus was the former frequent-flyer loyalty program of Air France before it was succeeded by Flying Blue.
  • D. Flurry
    Flurry is a mobile analytics and advertising platform known for providing app usage insights and monetization tools to developers.
  • E. La Fouine
    La Fouine is a French rapper and songwriter known for his influential role in the French hip-hop scene and his autobiographical, street-oriented lyrics.
  • 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: Le FCM
Triple: [FC Metz, nickName, Le FCM]
Generated description
Le FCM is the common nickname of FC Metz, a French professional football club based in Metz, Lorraine.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Le FCM
Target entity description: Le FCM is the common nickname of FC Metz, a French professional football club based in Metz, Lorraine.
  • A. Le DFCO
    Le DFCO is the commonly used nickname for Dijon FCO, a French professional football club based in Dijon.
  • B. Le MUC
    Le MUC is the commonly used nickname for the French football club Le Mans FC.
  • C. Fréquence Plus
    Fréquence Plus was the former frequent-flyer loyalty program of Air France before it was succeeded by Flying Blue.
  • D. Flurry
    Flurry is a mobile analytics and advertising platform known for providing app usage insights and monetization tools to developers.
  • E. La Fouine
    La Fouine is a French rapper and songwriter known for his influential role in the French hip-hop scene and his autobiographical, street-oriented lyrics.
  • 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_69d827980cbc8190a0c569ae3940a1d9 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69ded6070b248190be8f4f91a0c0b1f3 completed April 15, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b679fb081908cf8f41acfba3b99 completed May 8, 2026, 11:01 p.m.
NEDg Description generation batch_69fe6cc2ccb0819081e32dc9d2e3973a completed May 8, 2026, 11:07 p.m.
NED2 Entity disambiguation (via description) batch_69fe6d9e9a648190920206c8f75cae2e completed May 8, 2026, 11:11 p.m.
Created at: April 10, 2026, 2:10 a.m.