Triple

T2437086
Position Surface form Disambiguated ID Type / Status
Subject Brussels Airlines E52985 entity
Predicate ICAOCode P419 FINISHED
Object BEL
BEL is the ICAO airline designator used to identify Brussels Airlines in international aviation operations.
 E265980 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: BEL | Statement: [Brussels Airlines, ICAOCode, BEL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BEL
Context triple: [Brussels Airlines, ICAOCode, BEL]
  • A. BEL
    BEL is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies Belgium in international standards and data systems.
  • B. Bel
    Bel is a major Mesopotamian god, often identified with Marduk, revered as a supreme deity and lord of the heavens and earth in Babylonian religion.
  • C. BAL
    BAL is the Amtrak station code for Pennsylvania Station in Baltimore, Maryland, a major rail hub in the city’s transportation network.
  • D. BL
    BL is the vehicle registration code used on license plates for the Swiss canton of Basel-Landschaft.
  • E. BL
    BL is the postcode area in the United Kingdom that covers Bolton and surrounding parts of Greater Manchester and Lancashire.
  • 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: BEL
Triple: [Brussels Airlines, ICAOCode, BEL]
Generated description
BEL is the ICAO airline designator used to identify Brussels Airlines in international aviation operations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BEL
Target entity description: BEL is the ICAO airline designator used to identify Brussels Airlines in international aviation operations.
  • A. BEL
    BEL is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies Belgium in international standards and data systems.
  • B. Bel
    Bel is a major Mesopotamian god, often identified with Marduk, revered as a supreme deity and lord of the heavens and earth in Babylonian religion.
  • C. BAL
    BAL is the Amtrak station code for Pennsylvania Station in Baltimore, Maryland, a major rail hub in the city’s transportation network.
  • D. BL
    BL is the vehicle registration code used on license plates for the Swiss canton of Basel-Landschaft.
  • E. BL
    BL is the postcode area in the United Kingdom that covers Bolton and surrounding parts of Greater Manchester and Lancashire.
  • 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_69ab4959bcc0819083246f9fb10439e3 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc9f342e88190a430b02842ded418 completed March 7, 2026, 6:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf7085b88190938c4eefa4380970 completed March 9, 2026, 12:39 p.m.
NEDg Description generation batch_69aec30189d081908bb6865937aff20d completed March 9, 2026, 12:54 p.m.
NED2 Entity disambiguation (via description) batch_69aec39bb6a4819084652814e18f60d4 completed March 9, 2026, 12:56 p.m.
Created at: March 6, 2026, 9:43 p.m.