Triple

T6111698
Position Surface form Disambiguated ID Type / Status
Subject Paulina Connector E136256 entity
Predicate connects P390 FINISHED
Object Green Line E473596 NE FINISHED

How this triple was built (2 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: Green Line | Statement: [Paulina Connector, connects, Green Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Green Line
Context triple: [Paulina Connector, connects, Green Line]
  • A. Green Line
    The Green Line is one of the main rapid transit routes of the Dubai Metro, serving key districts along Dubai Creek and connecting important commercial and residential areas.
  • B. Green Line
    The Green Line is one of the main rapid transit corridors of the Chennai Metro system in Chennai, India, connecting key areas of the city via elevated and underground stations.
  • C. Green Line chosen
    The Green Line is one of the light rail routes in Houston’s METRORail system, serving the city’s East End and connecting it to downtown.
  • D. Green Line
    The Green Line is a light rail service within Salt Lake City's TRAX system that connects key destinations across the metropolitan area.
  • E. Green Line
    The Green Line is a light rail service route within the San Diego Trolley system that connects key destinations across the San Diego metropolitan area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c0089ea6f88190b349be53e04b4f5f completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05bbbbea88190b889a7c30af1d71a completed March 22, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5e3c26a9c8190a7dfbe0895461d3b completed March 27, 2026, 1:56 a.m.
Created at: March 22, 2026, 4:13 p.m.