Triple

T38131640
Position Surface form Disambiguated ID Type / Status
Subject Line 9–Emerald at Santo Amaro station E952237 entity
Predicate connectsLines P35490 FINISHED
Object Line 9–Emerald
Line 9–Emerald is a commuter rail line in São Paulo, Brazil, operated by CPTM and serving the city’s southwestern corridor along the Pinheiros River.
 E2258596 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: Line 9–Emerald | Statement: [Line 9–Emerald at Santo Amaro station, connectsLines, Line 9–Emerald]
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: Line 9–Emerald
Triple: [Line 9–Emerald at Santo Amaro station, connectsLines, Line 9–Emerald]
Generated description
Line 9–Emerald is a commuter rail line in São Paulo, Brazil, operated by CPTM and serving the city’s southwestern corridor along the Pinheiros River.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: connectsLines
Context triple: [Line 9–Emerald at Santo Amaro station, connectsLines, Line 9–Emerald]
  • A. connectedLine chosen
    Indicates that two entities are joined by a continuous line or linear connection.
  • B. connectsCitiesViaLine
    Indicates a relationship where a transportation line directly links two or more cities.
  • C. connectionLine
    Indicates a direct link or path that connects two entities within a system or structure.
  • D. networkLine
    Indicates that there is a connection or linkage between entities within a network structure or system.
  • E. connectsProvincesAlong
    Indicates a relationship where something serves as a link or route joining multiple provinces along a specified path or alignment.
  • 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_69f76f083548819082bd2bbf53c79e8e completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_6a00119d821c8190874786391b27ef23 completed May 10, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a4171227a6c81909827e303de40c8dc completed June 28, 2026, 7:08 p.m.
NEDg Description generation batch_6a41729eb5b0819092b897f73960804a completed June 28, 2026, 7:14 p.m.
NED2 Entity disambiguation (via description) batch_6a41730a3674819085411992e180a573 completed June 28, 2026, 7:16 p.m.
PD Predicate disambiguation batch_6a001143fb6881909ac0ae8bfea04351 completed May 10, 2026, 5:01 a.m.
Created at: May 3, 2026, 4:21 p.m.