Triple

T15558025
Position Surface form Disambiguated ID Type / Status
Subject Haugesund Airport Karmøy E370920 entity
Predicate ICAOcode P419 FINISHED
Object ENHD
ENHD is the ICAO airport code assigned to Haugesund Airport, Karmøy in Norway.
 E1163392 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: ENHD | Statement: [Haugesund Airport Karmøy, ICAOcode, ENHD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ENHD
Context triple: [Haugesund Airport Karmøy, ICAOcode, ENHD]
  • A. ENH
    ENH is the IATA airport code for Enshi Xujiaping Airport, a regional airport serving Enshi in Hubei Province, China.
  • B. ENHF
    ENHF is the ICAO airport code assigned to Hammerfest Airport in Norway.
  • C. EHE
    EHE is a U.S. federal public health initiative aimed at dramatically reducing new HIV infections and ultimately ending the HIV epidemic through targeted prevention, diagnosis, treatment, and response strategies.
  • D. EHE
    EHE is the commonly used abbreviation for the College of Education and Human Ecology, an academic unit focused on teaching, research, and outreach in education and human development fields.
  • E. HNE
    HNE is the abbreviation for Historic New England, a regional heritage organization dedicated to preserving and interpreting New England’s historic homes, landscapes, and cultural artifacts.
  • 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: ENHD
Triple: [Haugesund Airport Karmøy, ICAOcode, ENHD]
Generated description
ENHD is the ICAO airport code assigned to Haugesund Airport, Karmøy in Norway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ENHD
Target entity description: ENHD is the ICAO airport code assigned to Haugesund Airport, Karmøy in Norway.
  • A. ENH
    ENH is the IATA airport code for Enshi Xujiaping Airport, a regional airport serving Enshi in Hubei Province, China.
  • B. ENHF
    ENHF is the ICAO airport code assigned to Hammerfest Airport in Norway.
  • C. EHE
    EHE is a U.S. federal public health initiative aimed at dramatically reducing new HIV infections and ultimately ending the HIV epidemic through targeted prevention, diagnosis, treatment, and response strategies.
  • D. EHE
    EHE is the commonly used abbreviation for the College of Education and Human Ecology, an academic unit focused on teaching, research, and outreach in education and human development fields.
  • E. HNE
    HNE is the abbreviation for Historic New England, a regional heritage organization dedicated to preserving and interpreting New England’s historic homes, landscapes, and cultural artifacts.
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04dda3ab88190ab383333ce69fe8f completed April 16, 2026, 2:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff456635588190a2473bcff3ae4a53 completed May 9, 2026, 2:32 p.m.
NEDg Description generation batch_69ff46f44b2c81909f65f0ab455c6549 completed May 9, 2026, 2:38 p.m.
NED2 Entity disambiguation (via description) batch_69ff477a63b48190a453cf669dfda228 completed May 9, 2026, 2:40 p.m.
Created at: April 10, 2026, 4:09 a.m.