Triple

T20643631
Position Surface form Disambiguated ID Type / Status
Subject Moses Gate railway station E507293 entity
Predicate hasStationCode P1289 FINISHED
Object MSS NE NERFINISHED

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: MSS | Statement: [Moses Gate railway station, hasStationCode, MSS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MSS
Context triple: [Moses Gate railway station, hasStationCode, MSS]
  • A. MSS chosen
    MSS is the National Rail station code for Moses Gate railway station in Greater Manchester, England.
  • B. MSS
    MSS is the Mobile Servicing System, a Canadian-built robotic arm and handling system used on the International Space Station for assembly, maintenance, and payload operations.
  • C. Mss
    Mss is the station code for Maassluis railway station in the Netherlands.
  • D. MSSS
    MSSS is the acronym for Quebec’s Ministry of Health and Social Services, the provincial government body responsible for overseeing public health care and social services.
  • E. MSS (China)
    MSS (China) is the principal civilian intelligence, security, and secret police agency of the People's Republic of China, responsible for counterintelligence, foreign intelligence, and political security.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4be702c8190a3d2410a881d310a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6af1c51f48190abba54a5aace9fc8 completed April 20, 2026, 10:56 p.m.
Created at: April 16, 2026, 11:43 a.m.