Triple

T22320939
Position Surface form Disambiguated ID Type / Status
Subject Atocha Renfe E551781 entity
Predicate hasStationCode P1289 FINISHED
Object L1-AR
L1-AR is the specific station code assigned to the Atocha Renfe railway station in Madrid’s transport network.
 E1531803 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-AR | Statement: [Atocha Renfe, hasStationCode, L1-AR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: L1-AR
Context triple: [Atocha Renfe, hasStationCode, L1-AR]
  • A. L1
    L1 is the first Sun–Earth Lagrange point, a position in space where the gravitational forces of the Sun and Earth balance to allow a spacecraft to maintain a stable orbit between them.
  • B. L1
    L1 is the top professional football league in France, featuring the country’s highest-level clubs in the sport.
  • C. L10
    L10 is the pennant number assigned to HMS Fearless, a Royal Navy amphibious assault ship that served from the 1960s through the 1990s.
  • D. 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.
  • E. L1-SL
    L1-SL is the station code used to identify the San Lázaro stop on Line 1 of the Mexico City Metro system.
  • 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-AR
Triple: [Atocha Renfe, hasStationCode, L1-AR]
Generated description
L1-AR is the specific station code assigned to the Atocha Renfe railway station in Madrid’s transport network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: L1-AR
Target entity description: L1-AR is the specific station code assigned to the Atocha Renfe railway station in Madrid’s transport network.
  • A. L1
    L1 is the first Sun–Earth Lagrange point, a position in space where the gravitational forces of the Sun and Earth balance to allow a spacecraft to maintain a stable orbit between them.
  • B. L1
    L1 is the top professional football league in France, featuring the country’s highest-level clubs in the sport.
  • C. L10
    L10 is the pennant number assigned to HMS Fearless, a Royal Navy amphibious assault ship that served from the 1960s through the 1990s.
  • D. 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.
  • E. L1-SL
    L1-SL is the station code used to identify the San Lázaro stop on Line 1 of the Mexico City Metro 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_69e11e4776588190abb21e5cea79973f completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15764d3a48190af79ce4642b7f563 completed April 29, 2026, 12:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0ad51a87688190ad638880953172c7 completed May 18, 2026, 9 a.m.
NEDg Description generation batch_6a0ad991a1e48190ad240a20694223fc completed May 18, 2026, 9:19 a.m.
NED2 Entity disambiguation (via description) batch_6a0ada2a61b881908a636b2d1d6e4509 completed May 18, 2026, 9:21 a.m.
Created at: April 16, 2026, 8:42 p.m.