Triple

T17223221
Position Surface form Disambiguated ID Type / Status
Subject Florø E418042 entity
Predicate airportIATA P418 FINISHED
Object FRO
FRO is the IATA airport code for Florø Airport, a regional airport serving the town of Florø in western Norway.
E140587 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: FRO | Statement: [Florø, airportIATA, FRO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FRO
Context triple: [Florø, airportIATA, FRO]
  • A. FRO
    FRO is the three-letter ISO 3166-1 alpha-3 country code assigned to the Faroe Islands.
  • B. OFROU
    OFROU is the Swiss Federal Roads Office, the national authority responsible for planning, constructing, and maintaining Switzerland’s national road network and related traffic policies.
  • C. FO
    FO is the IATA airline designator assigned to Flybondi, a low-cost carrier based in Argentina.
  • D. FLO
    FLO is the Norwegian Defence Logistics Organisation, responsible for procuring, managing, and maintaining materiel and logistics support for Norway’s armed forces.
  • E. FRD
    FRD is the station code for a railway station named after U.S. President Franklin D. Roosevelt.
  • 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: FRO
Triple: [Florø, airportIATA, FRO]
Generated description
FRO is the IATA airport code for Florø Airport, a regional airport serving the town of Florø in western Norway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: FRO
Target entity description: FRO is the IATA airport code for Florø Airport, a regional airport serving the town of Florø in western Norway.
  • A. FRO chosen
    FRO is the three-letter ISO 3166-1 alpha-3 country code assigned to the Faroe Islands.
  • B. OFROU
    OFROU is the Swiss Federal Roads Office, the national authority responsible for planning, constructing, and maintaining Switzerland’s national road network and related traffic policies.
  • C. FO
    FO is the IATA airline designator assigned to Flybondi, a low-cost carrier based in Argentina.
  • D. FLO
    FLO is the Norwegian Defence Logistics Organisation, responsible for procuring, managing, and maintaining materiel and logistics support for Norway’s armed forces.
  • E. FRD
    FRD is the station code for a railway station named after U.S. President Franklin D. Roosevelt.
  • F. None of above.

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_69d886d779488190b131369541c04e7d completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42ddf2c3c8190b6adceaaefd4ccbf completed April 19, 2026, 1:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0167596ab481909df59ce68c7f640e completed May 11, 2026, 5:21 a.m.
NEDg Description generation batch_6a0169f4d520819095774ce5ee2d2220 completed May 11, 2026, 5:32 a.m.
NED2 Entity disambiguation (via description) batch_6a016a55114881909496549dfb7b6ff1 completed May 11, 2026, 5:34 a.m.
Created at: April 10, 2026, 5:38 a.m.