Triple

T23042139
Position Surface form Disambiguated ID Type / Status
Subject TS 27-series E573765 entity
Predicate appliesTo P1129 FINISHED
Object GSM systems E123436 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: GSM systems | Statement: [TS 27-series, appliesTo, GSM systems]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GSM systems
Context triple: [TS 27-series, appliesTo, GSM systems]
  • A. GSM
    GSM is the three-letter IATA airport code assigned to Qeshm International Airport in Iran.
  • B. GSM
    GSM is a classic Onitsuka Tiger sneaker model inspired by vintage tennis shoes, known for its minimalist design and retro athletic style.
  • C. GSM chosen
    GSM is a second-generation (2G) digital mobile communication standard that became the global foundation for cellular voice and basic data services.
  • D. GSM
    GSM is the common abbreviation for Great St Mary’s Church, the historic University Church located in the center of Cambridge, England.
  • E. GSM core network
    The GSM core network is the central backbone of GSM mobile systems, handling key functions such as switching, mobility management, authentication, and interconnection with other networks.
  • 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_69e245b9c11481909d06c872214d21af completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18516417081908bf747b20de23a75 completed April 29, 2026, 4:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c0ad85abc8190ab6328224aa3320f completed May 19, 2026, 7:01 a.m.
Created at: April 17, 2026, 3:54 p.m.