Triple

T3117482
Position Surface form Disambiguated ID Type / Status
Subject Lajes Airport E65096 entity
Predicate hasIATAcode P2569 FINISHED
Object TER
TER is the IATA airport code for Lajes Airport on Terceira Island in the Azores, Portugal.
 E329627 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: TER | Statement: [Lajes Airport, hasIATAcode, TER]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TER
Context triple: [Lajes Airport, hasIATAcode, TER]
  • A. TER
    TER is a network of regional express trains in France that provides local passenger rail services across various regions.
  • B. Ter
    The Ter is a river in northeastern Catalonia, Spain, that flows through cities such as Girona before emptying into the Mediterranean Sea.
  • C. TR
    TR is the two-letter ISO 3166-1 alpha-2 country code assigned to Turkey for international standardization and referencing.
  • D. TOR
    TOR is the standard three-letter abbreviation used to represent the Toronto Maple Leafs in sports standings, statistics, and media.
  • E. TOR
    TOR is the official code designation used for the Georgian football club FC Torpedo Kutaisi.
  • 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: TER
Triple: [Lajes Airport, hasIATAcode, TER]
Generated description
TER is the IATA airport code for Lajes Airport on Terceira Island in the Azores, Portugal.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TER
Target entity description: TER is the IATA airport code for Lajes Airport on Terceira Island in the Azores, Portugal.
  • A. TER
    TER is a network of regional express trains in France that provides local passenger rail services across various regions.
  • B. Ter
    The Ter is a river in northeastern Catalonia, Spain, that flows through cities such as Girona before emptying into the Mediterranean Sea.
  • C. TR
    TR is the two-letter ISO 3166-1 alpha-2 country code assigned to Turkey for international standardization and referencing.
  • D. TOR
    TOR is the standard three-letter abbreviation used to represent the Toronto Maple Leafs in sports standings, statistics, and media.
  • E. TOR
    TOR is the official code designation used for the Georgian football club FC Torpedo Kutaisi.
  • 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_69ad857fcc088190b0c4d45a5cde6f61 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada4e73cc88190846ef37ccf1a0de7 completed March 8, 2026, 4:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69b20f606fc881908754a78e6aa2de64 completed March 12, 2026, 12:57 a.m.
NEDg Description generation batch_69b2134b5eac8190adadc4a27cfe10c7 completed March 12, 2026, 1:13 a.m.
NED2 Entity disambiguation (via description) batch_69b216fcb1a881908edeadc639de31ae completed March 12, 2026, 1:29 a.m.
Created at: March 8, 2026, 3:04 p.m.