Triple

T3085720
Position Surface form Disambiguated ID Type / Status
Subject Mutare Airport E64367 entity
Predicate ICAOcode P419 FINISHED
Object FVMU
FVMU is the ICAO airport code assigned to Mutare Airport in Zimbabwe.
 E324755 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: FVMU | Statement: [Mutare Airport, ICAOcode, FVMU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FVMU
Context triple: [Mutare Airport, ICAOcode, FVMU]
  • A. FVBU
    FVBU is the ICAO airport code for Joshua Mqabuko Nkomo International Airport in Bulawayo, Zimbabwe.
  • B. VU
    VU is a major research university in Amsterdam, Netherlands, known for its wide range of academic programs and emphasis on interdisciplinary and socially engaged scholarship.
  • C. VMI
    VMI is a public military college in Lexington, Virginia, known for its rigorous academic and military training programs.
  • D. AMU
    The AMU, or Arab Maghreb Union, is a regional organization that promotes economic and political cooperation among North African Maghreb countries.
  • E. AMU
    AMU is the commonly used abbreviation for Aix-Marseille University, a major public research university in southern France.
  • 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: FVMU
Triple: [Mutare Airport, ICAOcode, FVMU]
Generated description
FVMU is the ICAO airport code assigned to Mutare Airport in Zimbabwe.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FVMU
Target entity description: FVMU is the ICAO airport code assigned to Mutare Airport in Zimbabwe.
  • A. FVBU
    FVBU is the ICAO airport code for Joshua Mqabuko Nkomo International Airport in Bulawayo, Zimbabwe.
  • B. VU
    VU is a major research university in Amsterdam, Netherlands, known for its wide range of academic programs and emphasis on interdisciplinary and socially engaged scholarship.
  • C. VMI
    VMI is a public military college in Lexington, Virginia, known for its rigorous academic and military training programs.
  • D. AMU
    The AMU, or Arab Maghreb Union, is a regional organization that promotes economic and political cooperation among North African Maghreb countries.
  • E. AMU
    AMU is the commonly used abbreviation for Aix-Marseille University, a major public research university in southern France.
  • 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_69ad857bb4c88190a4cf27893fcabed8 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada1eac5548190bee60ea8262c65a8 completed March 8, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1f89e6f5c8190993794e2c9977ee6 completed March 11, 2026, 11:19 p.m.
NEDg Description generation batch_69b1f93d5b208190835093f453fd33ab completed March 11, 2026, 11:22 p.m.
NED2 Entity disambiguation (via description) batch_69b1f9ea9b908190a86e2b79a89e0283 completed March 11, 2026, 11:25 p.m.
Created at: March 8, 2026, 3:03 p.m.