Triple

T9139803
Position Surface form Disambiguated ID Type / Status
Subject Estación Etiopía E219293 entity
Predicate hasStationCode P1289 FINISHED
Object ETI
ETI is the station code for Estación Etiopía, a metro station in Mexico City’s rapid transit system.
 E780628 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: ETI | Statement: [Estación Etiopía, hasStationCode, ETI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ETI
Context triple: [Estación Etiopía, hasStationCode, ETI]
  • A. ETAC
    ETAC is the Engineering Technology Accreditation Commission of ABET, responsible for accrediting engineering technology degree programs worldwide.
  • B. EETN
    EETN is the ICAO airport code for Lennart Meri Tallinn Airport, the main international airport serving Tallinn, Estonia.
  • C. ETB
    ETB is the three-letter international currency code used to represent the Ethiopian birr in global financial and foreign exchange contexts.
  • D. EIT
    EIT is a European Union body that fosters innovation, entrepreneurship, and education by integrating business, research, and higher education institutions across Europe.
  • E. METI
    METI (Messaging to Extra-Terrestrial Intelligence) is the scientific and philosophical endeavor focused on actively sending intentional signals into space to communicate with potential extraterrestrial civilizations.
  • 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: ETI
Triple: [Estación Etiopía, hasStationCode, ETI]
Generated description
ETI is the station code for Estación Etiopía, a metro station in Mexico City’s rapid transit system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ETI
Target entity description: ETI is the station code for Estación Etiopía, a metro station in Mexico City’s rapid transit system.
  • A. ETAC
    ETAC is the Engineering Technology Accreditation Commission of ABET, responsible for accrediting engineering technology degree programs worldwide.
  • B. EETN
    EETN is the ICAO airport code for Lennart Meri Tallinn Airport, the main international airport serving Tallinn, Estonia.
  • C. ETB
    ETB is the three-letter international currency code used to represent the Ethiopian birr in global financial and foreign exchange contexts.
  • D. EIT
    EIT is a European Union body that fosters innovation, entrepreneurship, and education by integrating business, research, and higher education institutions across Europe.
  • E. METI
    METI (Messaging to Extra-Terrestrial Intelligence) is the scientific and philosophical endeavor focused on actively sending intentional signals into space to communicate with potential extraterrestrial civilizations.
  • 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_69ca83e012288190a5771058adbaabd2 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca8f2537881908956a9b0516e2d49 completed April 1, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0480ee2f081908ed98844784e465c completed April 3, 2026, 11:06 p.m.
NEDg Description generation batch_69d04935d4e88190acb4d65a2dc2bc8a completed April 3, 2026, 11:11 p.m.
NED2 Entity disambiguation (via description) batch_69d049e6c4cc81909e08b5aaed9a88dc completed April 3, 2026, 11:14 p.m.
Created at: March 30, 2026, 7:19 p.m.