Triple

T7233353
Position Surface form Disambiguated ID Type / Status
Subject San Lázaro metro station E154956 entity
Predicate hasStationCode P1289 FINISHED
Object LAZ
LAZ is the station code for San Lázaro, a Mexico City Metro station serving Line 1 and Line B near the city’s eastern transport hubs.
 E650481 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: LAZ | Statement: [San Lázaro metro station, hasStationCode, LAZ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LAZ
Context triple: [San Lázaro metro station, hasStationCode, LAZ]
  • A. Laz
    Laz is a South Caucasian (Kartvelian) language traditionally spoken by the Laz people along the southeastern Black Sea coast, particularly in northeastern Turkey and parts of Georgia.
  • B. LAJ
    LAJ is the station code for La Junta station, an Amtrak railroad stop in La Junta, Colorado, serving long-distance passenger trains.
  • C. Lazi
    Lazi is a coastal municipality on the southeastern side of Siquijor Island in the Philippines, known for its historic church, natural springs, and waterfalls.
  • D. LZ
    LZ is the stock ticker symbol for The Lubrizol Corporation, a specialty chemicals company known for its lubricant additives and advanced materials.
  • E. LZ
    LZ is the vehicle registration code assigned to the municipality of Kals am Großglockner in Austria.
  • 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: LAZ
Triple: [San Lázaro metro station, hasStationCode, LAZ]
Generated description
LAZ is the station code for San Lázaro, a Mexico City Metro station serving Line 1 and Line B near the city’s eastern transport hubs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LAZ
Target entity description: LAZ is the station code for San Lázaro, a Mexico City Metro station serving Line 1 and Line B near the city’s eastern transport hubs.
  • A. Laz
    Laz is a South Caucasian (Kartvelian) language traditionally spoken by the Laz people along the southeastern Black Sea coast, particularly in northeastern Turkey and parts of Georgia.
  • B. LAJ
    LAJ is the station code for La Junta station, an Amtrak railroad stop in La Junta, Colorado, serving long-distance passenger trains.
  • C. Lazi
    Lazi is a coastal municipality on the southeastern side of Siquijor Island in the Philippines, known for its historic church, natural springs, and waterfalls.
  • D. LZ
    LZ is the stock ticker symbol for The Lubrizol Corporation, a specialty chemicals company known for its lubricant additives and advanced materials.
  • E. LZ
    LZ is the vehicle registration code assigned to the municipality of Kals am Großglockner in Austria.
  • 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_69c68811dd1c8190ac460bb39e64e1f0 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ea11b03c81909702ad2e0c29758a completed March 27, 2026, 8:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7cc2786f88190b0008891f801ca95 completed March 28, 2026, 12:40 p.m.
NEDg Description generation batch_69c7cd7cb5f081908c2ca7ce8653f25f completed March 28, 2026, 12:45 p.m.
NED2 Entity disambiguation (via description) batch_69c7cdf9e0608190a466ed638b728924 completed March 28, 2026, 12:47 p.m.
Created at: March 27, 2026, 2:55 p.m.