Triple

T3067586
Position Surface form Disambiguated ID Type / Status
Subject Hana Airport E62141 entity
Predicate ICAO code P419 FINISHED
Object PHHN
PHHN is the ICAO airport code for Hana Airport, a small public airport on the island of Maui in Hawaii.
 E322026 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: PHHN | Statement: [Hana Airport, ICAO code, PHHN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: PHHN
Context triple: [Hana Airport, ICAO code, PHHN]
  • A. PHNL
    PHNL is the ICAO airport code for Daniel K. Inouye International Airport, the main commercial aviation hub serving Honolulu and the state of Hawaii.
  • B. PHE
    PHE is the acronym for Public Health England, the former executive agency of the UK government responsible for protecting and improving the nation’s health and wellbeing.
  • C. PH
    PH is the vehicle registration code used on license plates for vehicles registered in Ploiești, Romania.
  • D. PPO2
    PPO2 is an improved variant of the Proximal Policy Optimization reinforcement learning algorithm, designed for stable and efficient policy gradient training in continuous and discrete control tasks.
  • E. PNE
    PNE is a professional football club based in Preston, Lancashire, England, known for being one of the founding members of the English Football League.
  • 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: PHHN
Triple: [Hana Airport, ICAO code, PHHN]
Generated description
PHHN is the ICAO airport code for Hana Airport, a small public airport on the island of Maui in Hawaii.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: PHHN
Target entity description: PHHN is the ICAO airport code for Hana Airport, a small public airport on the island of Maui in Hawaii.
  • A. PHNL
    PHNL is the ICAO airport code for Daniel K. Inouye International Airport, the main commercial aviation hub serving Honolulu and the state of Hawaii.
  • B. PHE
    PHE is the acronym for Public Health England, the former executive agency of the UK government responsible for protecting and improving the nation’s health and wellbeing.
  • C. PH
    PH is the vehicle registration code used on license plates for vehicles registered in Ploiești, Romania.
  • D. PPO2
    PPO2 is an improved variant of the Proximal Policy Optimization reinforcement learning algorithm, designed for stable and efficient policy gradient training in continuous and discrete control tasks.
  • E. PNE
    PNE is a professional football club based in Preston, Lancashire, England, known for being one of the founding members of the English Football League.
  • 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_69ad85793e5c8190a358049bc4a98d8c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada0fea06881909e5251eea26599ac completed March 8, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1ef1972e08190942a068c0c563e52 completed March 11, 2026, 10:39 p.m.
NEDg Description generation batch_69b1efa8c11081908661b33e465e11bc completed March 11, 2026, 10:41 p.m.
NED2 Entity disambiguation (via description) batch_69b1f062abf48190ab891463c5b33622 completed March 11, 2026, 10:44 p.m.
Created at: March 8, 2026, 3:02 p.m.