Triple

T8473360
Position Surface form Disambiguated ID Type / Status
Subject Line E (Buenos Aires Underground) E200331 entity
Predicate station P726 FINISHED
Object San José station
San José station is a stop on Buenos Aires’ Line E underground, serving passengers in the city’s central area.
 E740444 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: San José station | Statement: [Line E (Buenos Aires Underground), station, San José station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: San José station
Context triple: [Line E (Buenos Aires Underground), station, San José station]
  • A. San Ramón station
    San Ramón station is a stop on Santiago, Chile’s Metro system, serving passengers on Line 4A in the southeastern part of the city.
  • B. San Carlos station
    San Carlos station is a commuter rail station in San Carlos, California, serving Caltrain passengers on the San Francisco Peninsula.
  • C. Del Sol station
    Del Sol station is a stop on Santiago's Metro system serving Line 5 in the western part of Chile's capital.
  • D. Santa Clara station
    Santa Clara station is a Caltrain and Amtrak rail station in Santa Clara, California, serving as a key regional transit hub near San Jose.
  • E. Saenz Peña station
    Saenz Peña station is a stop on Line A of the Buenos Aires Underground, serving passengers in the central area of Argentina’s capital city.
  • 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: San José station
Triple: [Line E (Buenos Aires Underground), station, San José station]
Generated description
San José station is a stop on Buenos Aires’ Line E underground, serving passengers in the city’s central area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: San José station
Target entity description: San José station is a stop on Buenos Aires’ Line E underground, serving passengers in the city’s central area.
  • A. San Ramón station
    San Ramón station is a stop on Santiago, Chile’s Metro system, serving passengers on Line 4A in the southeastern part of the city.
  • B. San Carlos station
    San Carlos station is a commuter rail station in San Carlos, California, serving Caltrain passengers on the San Francisco Peninsula.
  • C. Del Sol station
    Del Sol station is a stop on Santiago's Metro system serving Line 5 in the western part of Chile's capital.
  • D. Santa Clara station
    Santa Clara station is a Caltrain and Amtrak rail station in Santa Clara, California, serving as a key regional transit hub near San Jose.
  • E. Saenz Peña station
    Saenz Peña station is a stop on Line A of the Buenos Aires Underground, serving passengers in the central area of Argentina’s capital city.
  • 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_69ca831a4f348190bfdd09250e86ae35 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe4f4fbf481909e4fd7c078b27477 completed March 31, 2026, 3:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6d019b748190a972ae32a56523c0 completed April 2, 2026, 1:20 p.m.
NEDg Description generation batch_69ce6e66c5e48190badcc5e075892006 completed April 2, 2026, 1:25 p.m.
NED2 Entity disambiguation (via description) batch_69ce6f0cc434819089e78d24dfee5361 completed April 2, 2026, 1:28 p.m.
Created at: March 30, 2026, 6:11 p.m.