Triple

T8005385
Position Surface form Disambiguated ID Type / Status
Subject Ligue 2 E186351 entity
Predicate governingBodyAbbreviation P2886 FINISHED
Object LFP
LFP is the French professional football league organization that oversees the top national divisions, including Ligue 1 and Ligue 2.
 E705398 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: LFP | Statement: [Ligue 2, governingBodyAbbreviation, LFP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LFP
Context triple: [Ligue 2, governingBodyAbbreviation, LFP]
  • A. LFP
    LFP is the commonly used abbreviation for Spain’s top professional football league organizer, La Liga (Liga Nacional de Fútbol Profesional).
  • B. LFPB
    LFPB is the ICAO airport code for Paris–Le Bourget Airport, a historic airfield near Paris known for business aviation and the Paris Air Show.
  • C. LNFP
    LNFP is the commonly used abbreviation for Spain’s top professional football league organizer, the Liga Nacional de Fútbol Profesional (La Liga).
  • D. LF
    LF is the commonly used abbreviation for the Linux Foundation, a nonprofit organization that supports and promotes the development of the Linux kernel and other open-source software projects.
  • E. LAP
    LAP is the ICAO airline designator used to identify LATAM Airlines Paraguay in international aviation operations.
  • 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: LFP
Triple: [Ligue 2, governingBodyAbbreviation, LFP]
Generated description
LFP is the French professional football league organization that oversees the top national divisions, including Ligue 1 and Ligue 2.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LFP
Target entity description: LFP is the French professional football league organization that oversees the top national divisions, including Ligue 1 and Ligue 2.
  • A. LFP
    LFP is the commonly used abbreviation for Spain’s top professional football league organizer, La Liga (Liga Nacional de Fútbol Profesional).
  • B. LFPB
    LFPB is the ICAO airport code for Paris–Le Bourget Airport, a historic airfield near Paris known for business aviation and the Paris Air Show.
  • C. LNFP
    LNFP is the commonly used abbreviation for Spain’s top professional football league organizer, the Liga Nacional de Fútbol Profesional (La Liga).
  • D. LF
    LF is the commonly used abbreviation for the Linux Foundation, a nonprofit organization that supports and promotes the development of the Linux kernel and other open-source software projects.
  • E. LAP
    LAP is the ICAO airline designator used to identify LATAM Airlines Paraguay in international aviation operations.
  • 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_69ca82aaaf24819084b94d18f699ba53 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3cf72fc08190aa78b97c1ab92f90 completed March 31, 2026, 3:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe127afe0819092d5ad0c430fadc4 completed March 31, 2026, 2:58 p.m.
NEDg Description generation batch_69cc46c221848190848c7e017e532a16 completed March 31, 2026, 10:12 p.m.
NED2 Entity disambiguation (via description) batch_69cc480d2f40819085046a1d0c9d05e0 completed March 31, 2026, 10:17 p.m.
Created at: March 30, 2026, 5:18 p.m.