Triple

T2923648
Position Surface form Disambiguated ID Type / Status
Subject Port Jefferson Branch E78791 entity
Predicate hasStation P35 FINISHED
Object Syosset station E90002 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: Syosset station | Statement: [Port Jefferson Branch, hasStation, Syosset station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Syosset station
Context triple: [Port Jefferson Branch, hasStation, Syosset station]
  • A. Syosset station chosen
    Syosset station is a Long Island Rail Road commuter rail stop serving the community of Syosset in Nassau County, New York.
  • B. Osakajokoen Station
    Osakajokoen Station is a railway station in Osaka, Japan that serves as a primary access point for visitors to Osaka Castle and its surrounding park.
  • C. Santolan station
    Santolan station is an elevated terminal station of Manila's LRT Line 2 serving commuters in the eastern part of Metro Manila, Philippines.
  • D. Kommunarka station
    Kommunarka station is a southern terminal metro station on Moscow’s Sokolnicheskaya Line, serving the rapidly developing Kommunarka district.
  • E. Majorstuen station
    Majorstuen station is a key interchange on the Oslo Metro where multiple lines converge, serving as a major transit hub in the western part of the city.
  • 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_69ad8b0d40b481908bc2a5fa2e73c3fb completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad97bf2df88190bd4f1e90d4656507 completed March 8, 2026, 3:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69b056375b5c819081c7d4fd506cbf25 completed March 10, 2026, 5:34 p.m.
Created at: March 8, 2026, 2:55 p.m.