Triple

T3468153
Position Surface form Disambiguated ID Type / Status
Subject Turin Airport E73186 entity
Predicate ICAOcode P419 FINISHED
Object LIMF
LIMF is the ICAO airport code for Turin Airport, an international airport serving the city of Turin in northern Italy.
 E361834 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: LIMF | Statement: [Turin Airport, ICAOcode, LIMF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LIMF
Context triple: [Turin Airport, ICAOcode, LIMF]
  • A. LIM
    LIM is the IATA airport code for Jorge Chávez International Airport, the main international gateway serving Lima, Peru.
  • B. LIMC
    LIMC is the ICAO airport code for Milan Malpensa Airport, a major international airport serving the Milan metropolitan area in Italy.
  • C. LIF
    LIF is the vehicle registration code for the town and district of Lichtenfels in the German state of Bavaria.
  • D. Lim-5
    The Lim-5 is a Polish-built version of the Soviet MiG-17 jet fighter, produced under license and used primarily by the Polish Air Force during the Cold War.
  • E. Lim
    Lim is a Korean surname borne by numerous notable individuals across fields such as politics, academia, and the arts.
  • 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: LIMF
Triple: [Turin Airport, ICAOcode, LIMF]
Generated description
LIMF is the ICAO airport code for Turin Airport, an international airport serving the city of Turin in northern Italy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LIMF
Target entity description: LIMF is the ICAO airport code for Turin Airport, an international airport serving the city of Turin in northern Italy.
  • A. LIM
    LIM is the IATA airport code for Jorge Chávez International Airport, the main international gateway serving Lima, Peru.
  • B. LIMC
    LIMC is the ICAO airport code for Milan Malpensa Airport, a major international airport serving the Milan metropolitan area in Italy.
  • C. LIF
    LIF is the vehicle registration code for the town and district of Lichtenfels in the German state of Bavaria.
  • D. Lim-5
    The Lim-5 is a Polish-built version of the Soviet MiG-17 jet fighter, produced under license and used primarily by the Polish Air Force during the Cold War.
  • E. Lim
    Lim is a Korean surname borne by numerous notable individuals across fields such as politics, academia, and the arts.
  • 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_69ad85b224d481908ff8be51338d24ff completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbb11ec5881908347bf92883a25ee completed March 8, 2026, 6:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3680763608190acdd146dc7c0b239 completed March 13, 2026, 1:27 a.m.
NEDg Description generation batch_69b36c4d77448190abe198ec9d48597d completed March 13, 2026, 1:45 a.m.
NED2 Entity disambiguation (via description) batch_69b36cca06d48190bc72ad2e9bd9bdb5 completed March 13, 2026, 1:47 a.m.
Created at: March 8, 2026, 3:17 p.m.