Triple

T16442260
Position Surface form Disambiguated ID Type / Status
Subject CTA rail network E399332 entity
Predicate hasStation P35 FINISHED
Object State/Lake E366593 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: State/Lake | Statement: [CTA rail network, hasStation, State/Lake]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: State/Lake
Context triple: [CTA rail network, hasStation, State/Lake]
  • A. State/Lake chosen
    State/Lake is an elevated Chicago 'L' station in the Loop that serves the Brown Line and several other CTA train lines.
  • B. Stan State
    Stan State is the commonly used name for California State University, Stanislaus, a public university in Turlock, California, known for its diverse academic programs and regional impact.
  • C. Morvee State
    Morvee State is a former princely state in western India, historically located in present-day Gujarat.
  • D. Aimeliik State
    Aimeliik State is one of the states of Palau, located on the western side of the island of Babeldaob and known for its traditional villages and coastal mangrove forests.
  • E. State
    State is a behavioral design pattern that lets an object alter its behavior when its internal state changes, making it appear as if the object has changed its class.
  • 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_69d87f2c6778819080fcfae53be8f12a completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32ba91dc48190bc35db60f63d36d3 completed April 18, 2026, 6:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00458f8f3c8190ad5eff2ad2a32dea completed May 10, 2026, 8:45 a.m.
Created at: April 10, 2026, 5:10 a.m.