Triple

T29907322
Position Surface form Disambiguated ID Type / Status
Subject Humaitá, Rio de Janeiro, Brazil E759573 entity
Predicate closestMetroStation P26735 FINISHED
Object Botafogo Station
Botafogo Station is a major Rio de Janeiro Metro stop in the South Zone that serves the Botafogo and nearby Humaitá neighborhoods.
 E1893425 NE FINISHED

How this triple was built (3 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: Botafogo Station | Statement: [Humaitá, Rio de Janeiro, Brazil, closestMetroStation, Botafogo Station]
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: Botafogo Station
Triple: [Humaitá, Rio de Janeiro, Brazil, closestMetroStation, Botafogo Station]
Generated description
Botafogo Station is a major Rio de Janeiro Metro stop in the South Zone that serves the Botafogo and nearby Humaitá neighborhoods.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: closestMetroStation
Context triple: [Humaitá, Rio de Janeiro, Brazil, closestMetroStation, Botafogo Station]
  • A. nearMetroStation
    Indicates that one entity is located close to or within a short walking distance of a metro (subway) station.
  • B. nearestSuburbanRailwayStation
    Indicates the relationship where a given place is associated with the suburban railway station that is geographically closest to it.
  • C. nearestEntranceStation
    Indicates that one station is the closest entrance station to a given location or entity compared to all other candidate stations.
  • D. nearestUndergroundStation chosen
    Indicates the relationship where a specific underground (subway/metro) station is the closest one in distance to a given location or entity.
  • E. nearestMajorMetro
    Indicates the relationship where a given location is associated with the closest large metropolitan area to it.
  • F. None of above.

Provenance (6 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_69f224600590819085e148a01c056ef6 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f7308a096081909d66a56f3c926806 completed May 3, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2721e3d6588190bffbeb1a9cf79f40 completed June 8, 2026, 8:11 p.m.
NEDg Description generation batch_6a27226c29fc81909e79cb508975bc92 completed June 8, 2026, 8:13 p.m.
NED2 Entity disambiguation (via description) batch_6a27231dfdac8190870ab5105b8c174d completed June 8, 2026, 8:16 p.m.
PD Predicate disambiguation batch_69f72a00c5f081908b6539d15baf4e12 completed May 3, 2026, 10:57 a.m.
Created at: April 29, 2026, 6:09 p.m.