Triple

T3184443
Position Surface form Disambiguated ID Type / Status
Subject Ligue 1 E66666 entity
Predicate abbreviation P43 FINISHED
Object L1
L1 is the top professional football league in France, featuring the country’s highest-level clubs in the sport.
E334364 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: L1 | Statement: [Ligue 1, abbreviation, L1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: L1
Context triple: [Ligue 1, abbreviation, L1]
  • A. L1-SL
    L1-SL is the station code used to identify the San Lázaro stop on Line 1 of the Mexico City Metro system.
  • B. L1BC
    L1BC is a regional Canadian soccer league that operates as part of the League1 Canada structure, providing a pro-am development platform for players in British Columbia.
  • C. L1O
    L1O is a Canadian pro-am soccer league in Ontario that forms part of the country’s third tier in the men’s and women’s soccer pyramid.
  • D. L
    L is the vehicle registration code used on license plates for the German city and district of Leipzig.
  • E. L
    The L is a New York City Subway line that runs crosstown through Manhattan and into Brooklyn, including service to neighborhoods such as Canarsie.
  • 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: L1
Triple: [Ligue 1, abbreviation, L1]
Generated description
L1 is the top professional football league in France, featuring the country’s highest-level clubs in the sport.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: L1
Target entity description: L1 is the top professional football league in France, featuring the country’s highest-level clubs in the sport.
  • A. L1-SL
    L1-SL is the station code used to identify the San Lázaro stop on Line 1 of the Mexico City Metro system.
  • B. L1BC
    L1BC is a regional Canadian soccer league that operates as part of the League1 Canada structure, providing a pro-am development platform for players in British Columbia.
  • C. L1O
    L1O is a Canadian pro-am soccer league in Ontario that forms part of the country’s third tier in the men’s and women’s soccer pyramid.
  • D. L
    L is the enigmatic, emotionally complex protagonist of Hanne Ørstavik’s novel "Love," whose inner life and perspective drive the story’s exploration of isolation and longing.
  • E. L
    The L is a Chicago 'L' rapid transit line that serves the city’s West Side and western suburbs as part of the Chicago Transit Authority system.
  • 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_69ad8587c1bc8190a2595f2c22ee1001 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada6bfc4248190af320471688c60f0 completed March 8, 2026, 4:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69b236039b148190ab581709cfcfcd01 completed March 12, 2026, 3:41 a.m.
NEDg Description generation batch_69b239d78e808190b53d2ba93ed0e667 completed March 12, 2026, 3:58 a.m.
NED2 Entity disambiguation (via description) batch_69b23a4598e481908fc64c5c0bf46427 completed March 12, 2026, 4 a.m.
Created at: March 8, 2026, 3:06 p.m.