Triple

T12441208
Position Surface form Disambiguated ID Type / Status
Subject Hua Mak station E297273 entity
Predicate hasStationCode P1289 FINISHED
Object A3
A3 is the station code assigned to Hua Mak station on Bangkok’s Airport Rail Link transit system.
 E984339 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: A3 | Statement: [Hua Mak station, hasStationCode, A3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: A3
Context triple: [Hua Mak station, hasStationCode, A3]
  • A. A3
    A3 is a major national highway in Zimbabwe that serves as an important route connecting key towns and regions within the country.
  • B. A3
    A3 is a major Swiss motorway that runs across the country’s north, connecting key cities and regions as part of the national highway network.
  • C. A3
    A3 is a British band best known for its eclectic fusion of rock, electronic, blues, and country influences, including the song used as the theme for the TV series "The Sopranos."
  • D. A3
    A3 is a major German autobahn that runs across several federal states, serving as an important east–west transport corridor.
  • E. A3
    A3 is the IATA airline designator for Aegean Airlines, the largest Greek airline and a member of the Star Alliance.
  • 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: A3
Triple: [Hua Mak station, hasStationCode, A3]
Generated description
A3 is the station code assigned to Hua Mak station on Bangkok’s Airport Rail Link transit system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: A3
Target entity description: A3 is the station code assigned to Hua Mak station on Bangkok’s Airport Rail Link transit system.
  • A. A3
    A3 is a French autoroute designation for a major motorway segment within the national highway network.
  • B. A3
    A3 is the IATA airline designator for Aegean Airlines, the largest Greek airline and a member of the Star Alliance.
  • C. A3
    A3 is a major Swiss motorway that runs across the country’s north, connecting key cities and regions as part of the national highway network.
  • D. A3
    A3 is a major national highway in Zimbabwe that serves as an important route connecting key towns and regions within the country.
  • E. A3
    A3 is a major German autobahn that runs across several federal states, serving as an important east–west transport corridor.
  • 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_69d6ada166c48190b902972cd2408fa3 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d8ecb6c8190a19cbf9de31cabbd completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f0ea1e48190a11cf94797290156 completed May 2, 2026, 6:14 p.m.
NEDg Description generation batch_69f64010a1348190afaf7b95b8f146b5 completed May 2, 2026, 6:18 p.m.
NED2 Entity disambiguation (via description) batch_69f640c33d948190ad8f9885f90786d7 completed May 2, 2026, 6:21 p.m.
Created at: April 8, 2026, 9:55 p.m.