Triple

T11894018
Position Surface form Disambiguated ID Type / Status
Subject Line 15–Silver E282989 entity
Predicate station P726 FINISHED
Object Sapopemba
Sapopemba is a metro station on São Paulo’s Line 15–Silver monorail, serving the Sapopemba district in the city’s eastern zone.
 E952243 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: Sapopemba | Statement: [Line 15–Silver, station, Sapopemba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sapopemba
Context triple: [Line 15–Silver, station, Sapopemba]
  • A. Tangub
    Tangub is a coastal city in Misamis Occidental, Philippines, known for its location along Iligan Bay and its festive Christmas decorations.
  • B. Sutera
    Sutera is a historic hilltop town in central Sicily, Italy, known for its medieval architecture and panoramic views over the surrounding countryside.
  • C. Gundunguri
    Gundunguri is an alternative name for the Gundungurra, an Aboriginal Australian people traditionally associated with the Southern Highlands and Blue Mountains region of New South Wales.
  • D. Pakurumo
    Pakurumo is a popular Afrobeat song by Nigerian artist Wizkid, known for its upbeat rhythm and dance-friendly vibe.
  • E. Palaonda
    Palaonda is an indoor ice arena in Bolzano, Italy, primarily used for ice hockey and other sporting and entertainment events.
  • 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: Sapopemba
Triple: [Line 15–Silver, station, Sapopemba]
Generated description
Sapopemba is a metro station on São Paulo’s Line 15–Silver monorail, serving the Sapopemba district in the city’s eastern zone.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sapopemba
Target entity description: Sapopemba is a metro station on São Paulo’s Line 15–Silver monorail, serving the Sapopemba district in the city’s eastern zone.
  • A. Tangub
    Tangub is a coastal city in Misamis Occidental, Philippines, known for its location along Iligan Bay and its festive Christmas decorations.
  • B. Sutera
    Sutera is a historic hilltop town in central Sicily, Italy, known for its medieval architecture and panoramic views over the surrounding countryside.
  • C. Gundunguri
    Gundunguri is an alternative name for the Gundungurra, an Aboriginal Australian people traditionally associated with the Southern Highlands and Blue Mountains region of New South Wales.
  • D. Pakurumo
    Pakurumo is a popular Afrobeat song by Nigerian artist Wizkid, known for its upbeat rhythm and dance-friendly vibe.
  • E. Palaonda
    Palaonda is an indoor ice arena in Bolzano, Italy, primarily used for ice hockey and other sporting and entertainment events.
  • 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_69d6ab2a90b08190a4e818821cc93e6d completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8dd1172988190a2c13d37220f2f93 completed April 10, 2026, 11:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69f4180569ac81909137d56374e800c0 completed May 1, 2026, 3:03 a.m.
NEDg Description generation batch_69f41f1abaa481908b8a6873a07af848 completed May 1, 2026, 3:33 a.m.
NED2 Entity disambiguation (via description) batch_69f42283c4cc81909793834ef65d2514 completed May 1, 2026, 3:48 a.m.
Created at: April 8, 2026, 9:44 p.m.