Triple

T5481376
Position Surface form Disambiguated ID Type / Status
Subject GSM core network E123472 entity
Predicate usesDatabase P11852 FINISHED
Object HLR E523114 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: HLR | Statement: [GSM core network, usesDatabase, HLR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HLR
Context triple: [GSM core network, usesDatabase, HLR]
  • A. HLR chosen
    HLR (Home Location Register) is a central database in mobile networks that stores and manages subscriber information, authentication data, and location details for GSM users.
  • B. VLR
    VLR is the abbreviation for the Virginia Landmarks Register, the Commonwealth of Virginia’s official list of historically significant properties and districts.
  • C. VLR
    VLR (Visitor Location Register) is a key mobile network database that temporarily stores subscriber information and location details for users currently roaming within a specific area.
  • D. HRL
    HRL is a renowned research center known for pioneering work in fields such as microelectronics, information and quantum sciences, and advanced materials.
  • E. HL
    HL is the vehicle registration code used on license plates for the German city of Lübeck.
  • 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_69bd4648883481909e9775d43300c5fa completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd924a2eb08190b759b23a6eab5e0a completed March 20, 2026, 6:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf6c812d4c8190a22f76b787ab0f10 completed March 22, 2026, 4:13 a.m.
Created at: March 20, 2026, 2:09 p.m.