Triple

T91489
Position Surface form Disambiguated ID Type / Status
Subject Terminal 5 E1837 entity
Predicate alsoKnownAs P39 FINISHED
Object T5
T5 is a major passenger terminal at London Heathrow Airport, primarily serving British Airways and Iberia flights.
 E7849 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: T5 | Statement: [Terminal 5, alsoKnownAs, T5]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: T5
Context triple: [Terminal 5, alsoKnownAs, T5]
  • A. TEC
    TEC is the commonly used acronym for the Episcopal Church, a mainline Anglican Christian denomination based in the United States.
  • B. TNT
    TNT is an American cable television network known for airing sports, movies, and original drama programming.
  • C. PT
    PT is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Portugal in international standards and systems.
  • D. Kt
    Kt is the post-nominal abbreviation used to denote a Knight Bachelor in the British honours system.
  • E. TRST
    TRST is an optional active-low reset signal used in JTAG (IEEE 1149.1) interfaces to asynchronously reset the test access port controller.
  • 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: T5
Triple: [Terminal 5, alsoKnownAs, T5]
Generated description
T5 is a major passenger terminal at London Heathrow Airport, primarily serving British Airways and Iberia flights.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: T5
Target entity description: T5 is a major passenger terminal at London Heathrow Airport, primarily serving British Airways and Iberia flights.
  • A. TEC
    TEC is the commonly used acronym for the Episcopal Church, a mainline Anglican Christian denomination based in the United States.
  • B. TNT
    TNT is an American cable television network known for airing sports, movies, and original drama programming.
  • C. PT
    PT is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Portugal in international standards and systems.
  • D. Kt
    Kt is the post-nominal abbreviation used to denote a Knight Bachelor in the British honours system.
  • E. TRST
    TRST is an optional active-low reset signal used in JTAG (IEEE 1149.1) interfaces to asynchronously reset the test access port controller.
  • 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_69a24d1a97dc819094e6c021fe9b05a7 completed Feb. 28, 2026, 2:04 a.m.
NER Named-entity recognition batch_69a24f6c29888190890caa7872d63ac6 completed Feb. 28, 2026, 2:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69a26245bf748190828d5cb4624b2a79 completed Feb. 28, 2026, 3:34 a.m.
NEDg Description generation batch_69a262bec71481909b251923011ca502 completed Feb. 28, 2026, 3:36 a.m.
NED2 Entity disambiguation (via description) batch_69a263626b7c8190b53469d93ac604d9 completed Feb. 28, 2026, 3:39 a.m.
Created at: Feb. 28, 2026, 2:07 a.m.