Triple

T5481347
Position Surface form Disambiguated ID Type / Status
Subject GSM core network E123472 entity
Predicate includesElement P11236 FINISHED
Object HLR
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.
 E523114 NE FINISHED

How this triple was built (4 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, includesElement, HLR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HLR
Context triple: [GSM core network, includesElement, HLR]
  • A. HRL
    HRL is a renowned research center known for pioneering work in fields such as microelectronics, information and quantum sciences, and advanced materials.
  • B. HL
    HL is the vehicle registration code used on license plates for the German city of Lübeck.
  • C. HEL
    HEL is the three-letter IATA airport code for Helsinki Airport, the main international gateway to Finland’s capital region.
  • D. HRP
    HRP is a high-level long-distance hiking route that traverses the Pyrenees along or near the French–Spanish border from the Atlantic Ocean to the Mediterranean Sea.
  • E. HLC
    HLC is the commonly used abbreviation for the Harvard Longwood Campus, a major Harvard University hub for medical and public health education and research in Boston.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: HLR
Triple: [GSM core network, includesElement, HLR]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HLR
Target entity description: 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.
  • A. HRL
    HRL is a renowned research center known for pioneering work in fields such as microelectronics, information and quantum sciences, and advanced materials.
  • B. HL
    HL is the vehicle registration code used on license plates for the German city of Lübeck.
  • C. HEL
    HEL is the three-letter IATA airport code for Helsinki Airport, the main international gateway to Finland’s capital region.
  • D. HRP
    HRP is a high-level long-distance hiking route that traverses the Pyrenees along or near the French–Spanish border from the Atlantic Ocean to the Mediterranean Sea.
  • E. HLC
    HLC is the commonly used abbreviation for the Harvard Longwood Campus, a major Harvard University hub for medical and public health education and research in Boston.
  • F. None of above. chosen

Provenance (5 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_69bf48a2880c8190ad76cf8c3862aede completed March 22, 2026, 1:40 a.m.
NEDg Description generation batch_69bf4a95375881909ba730ad108eee8b completed March 22, 2026, 1:49 a.m.
NED2 Entity disambiguation (via description) batch_69bf4afb47a88190a66de6b6c7d5c241 completed March 22, 2026, 1:50 a.m.
Created at: March 20, 2026, 2:09 p.m.