Triple

T12050226
Position Surface form Disambiguated ID Type / Status
Subject Line 4–Yellow E286895 entity
Predicate terminusStation P15150 FINISHED
Object Luz
Luz is a major railway and metro hub in São Paulo, Brazil, serving as a key interchange point for multiple urban transit lines.
 E967162 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: Luz | Statement: [Line 4–Yellow, terminusStation, Luz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Luz
Context triple: [Line 4–Yellow, terminusStation, Luz]
  • A. Luz
    Luz is a small coastal settlement on Graciosa Island in Portugal’s Azores archipelago.
  • B. Luz
    Luz is a historic neighborhood in Chennai, India, known for its cultural landmarks and proximity to the coastal Santhome area.
  • C. Luci
    Luci is a diminutive form of the given name Luciana, often used as a familiar or affectionate nickname.
  • D. Luce
    Luce is a surname most notably associated with Henry Luce, the influential American magazine magnate and co-founder of Time Inc.
  • E. Luce
    Luce is the abbreviated name of Italy’s historic Istituto Nazionale Luce, a state film and newsreel institute known for producing and distributing documentary and propaganda films.
  • 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: Luz
Triple: [Line 4–Yellow, terminusStation, Luz]
Generated description
Luz is a major railway and metro hub in São Paulo, Brazil, serving as a key interchange point for multiple urban transit lines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Luz
Target entity description: Luz is a major railway and metro hub in São Paulo, Brazil, serving as a key interchange point for multiple urban transit lines.
  • A. Luz
    Luz is a small coastal settlement on Graciosa Island in Portugal’s Azores archipelago.
  • B. Luz
    Luz is a historic neighborhood in Chennai, India, known for its cultural landmarks and proximity to the coastal Santhome area.
  • C. Luci
    Luci is a diminutive form of the given name Luciana, often used as a familiar or affectionate nickname.
  • D. Luce
    Luce is a surname most notably associated with Henry Luce, the influential American magazine magnate and co-founder of Time Inc.
  • E. Luce
    Luce is the abbreviated name of Italy’s historic Istituto Nazionale Luce, a state film and newsreel institute known for producing and distributing documentary and propaganda films.
  • 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_69d6ab4780948190bdb9f7620c2ac27e completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d904227958819084dbd5eb2566c735 completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f64d12b48190a041d6782c6a13e0 completed May 2, 2026, 1:04 p.m.
NEDg Description generation batch_69f6037933708190b80c6b0f874f9786 completed May 2, 2026, 2 p.m.
NED2 Entity disambiguation (via description) batch_69f604501eec8190a6f3cafef76b5f2c completed May 2, 2026, 2:04 p.m.
Created at: April 8, 2026, 9:47 p.m.