Triple

T6718928
Position Surface form Disambiguated ID Type / Status
Subject SIX Swiss Exchange E153343 entity
Predicate clearingAndSettlementProvider P5407 FINISHED
Object SIX x-clear E536945 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: SIX x-clear | Statement: [SIX Swiss Exchange, clearingAndSettlementProvider, SIX x-clear]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SIX x-clear
Context triple: [SIX Swiss Exchange, clearingAndSettlementProvider, SIX x-clear]
  • A. SIX x-clear chosen
    SIX x-clear is a central counterparty clearing house operated by SIX Group that provides clearing services for various financial instruments traded on European exchanges.
  • B. SIX:CSGN
    SIX:CSGN is the former stock ticker symbol on the SIX Swiss Exchange for Credit Suisse Group, a major Swiss financial services and investment banking institution.
  • C. St Clears
    St Clears is a small town and community in Carmarthenshire, Wales, known for its historic abbey remains and position near the River Taf.
  • D. Clearing
    Clearing is a residential and industrial neighborhood on the southwest side of Chicago, known for encompassing and surrounding Midway International Airport.
  • E. Clearing
    "Clearing" is a large-scale photographic work by German artist Thomas Demand, known for its meticulously constructed paper model of a forest scene that blurs the line between reality and fabrication.
  • 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_69c68809b4608190a2509ddb5ab87f05 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d135d27c819088c45839ad0e7bab completed March 27, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7009b9b64819095ae1a65cd72c374 completed March 27, 2026, 10:11 p.m.
Created at: March 27, 2026, 2:07 p.m.