Triple

T13248917
Position Surface form Disambiguated ID Type / Status
Subject Lower Sydenham railway station E315475 entity
Predicate hasTicketingSystem P3383 FINISHED
Object Oyster E293568 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: Oyster | Statement: [Lower Sydenham railway station, hasTicketingSystem, Oyster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oyster
Context triple: [Lower Sydenham railway station, hasTicketingSystem, Oyster]
  • A. Oyster chosen
    Oyster is a contactless smartcard used for paying fares on public transport in London.
  • B. Mejillones
    Mejillones is a coastal Chilean port city on the Pacific Ocean, known for its fishing industry and role in regional maritime trade.
  • C. Shrimp
    Shrimp was the code name for the high-yield, solid-fueled thermonuclear device detonated in the United States' 1954 Castle Bravo nuclear test at Bikini Atoll.
  • D. Lamut
    Lamut is an indigenous Siberian people of northeastern Russia, more commonly known as the Even.
  • E. Dungeness crab
    The Dungeness crab is a large, commercially important crab species native to the Pacific coast of North America, prized for its sweet, tender meat.
  • 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_69d806b1072881909e46bd212259c5f0 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98d9e7ea881908abc4b3a54896692 completed April 10, 2026, 11:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69f70a3b8ca48190863aff25f12d0e7e completed May 3, 2026, 8:41 a.m.
Created at: April 9, 2026, 9:24 p.m.