Triple

T8010811
Position Surface form Disambiguated ID Type / Status
Subject Hood Army Airfield E186485 entity
Predicate hasFAAIdentifier P420 FINISHED
Object HLR
HLR is the FAA location identifier for Hood Army Airfield, a U.S. Army aviation facility.
 E707357 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: [Hood Army Airfield, hasFAAIdentifier, HLR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HLR
Context triple: [Hood Army Airfield, hasFAAIdentifier, HLR]
  • A. 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.
  • 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. 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: [Hood Army Airfield, hasFAAIdentifier, HLR]
Generated description
HLR is the FAA location identifier for Hood Army Airfield, a U.S. Army aviation facility.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HLR
Target entity description: HLR is the FAA location identifier for Hood Army Airfield, a U.S. Army aviation facility.
  • A. 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.
  • 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. 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_69ca82abaffc8190ab8af79cdbc31ab3 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3d70caf8819090a9f98025470c0d completed March 31, 2026, 3:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc56a54e8081908208b57b7390cc95 completed March 31, 2026, 11:20 p.m.
NEDg Description generation batch_69cc58ecd0608190ab0880992bc203fb completed March 31, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_69cc5cb791b48190bd5004b518d23f84 completed March 31, 2026, 11:45 p.m.
Created at: March 30, 2026, 5:19 p.m.