Triple

T15775546
Position Surface form Disambiguated ID Type / Status
Subject Annan railway station E382479 entity
Predicate hasStationCode P1289 FINISHED
Object ANN
ANN is the National Rail station code for Annan railway station in Dumfries and Galloway, Scotland.
 E1175676 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: ANN | Statement: [Annan railway station, hasStationCode, ANN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ANN
Context triple: [Annan railway station, hasStationCode, ANN]
  • A. NN
    NN is the postcode area in the United Kingdom that covers Northampton and surrounding parts of Northamptonshire.
  • B. .ai
    .ai is the country code top-level domain (ccTLD) associated with Anguilla that has become popular worldwide for artificial intelligence-related websites.
  • C. ANA
    ANA is the standard three-letter abbreviation used for the Anaheim Ducks, a professional ice hockey team in the National Hockey League.
  • D. ANA
    ANA is the commonly used abbreviation for the Afghan National Army, the former main land warfare branch of Afghanistan’s armed forces.
  • E. ANA
    ANA is the ICAO airline designator for All Nippon Airways, Japan’s largest airline and a major global carrier.
  • 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: ANN
Triple: [Annan railway station, hasStationCode, ANN]
Generated description
ANN is the National Rail station code for Annan railway station in Dumfries and Galloway, Scotland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ANN
Target entity description: ANN is the National Rail station code for Annan railway station in Dumfries and Galloway, Scotland.
  • A. NN
    NN is the postcode area in the United Kingdom that covers Northampton and surrounding parts of Northamptonshire.
  • B. .ai
    .ai is the country code top-level domain (ccTLD) associated with Anguilla that has become popular worldwide for artificial intelligence-related websites.
  • C. ANA
    ANA is the standard three-letter abbreviation used for the Anaheim Ducks, a professional ice hockey team in the National Hockey League.
  • D. ANA
    ANA is the commonly used abbreviation for the Afghan National Army, the former main land warfare branch of Afghanistan’s armed forces.
  • E. ANA
    ANA is the ICAO airline designator for All Nippon Airways, Japan’s largest airline and a major global carrier.
  • 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_69d86da09a10819082fe9797b23e4664 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e05198c1588190a65e23c18443eb5c completed April 16, 2026, 3:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff877e67b881908a67b9acc79d998f completed May 9, 2026, 7:14 p.m.
NEDg Description generation batch_69ff88358e408190a8d7424fc495d4fa completed May 9, 2026, 7:17 p.m.
NED2 Entity disambiguation (via description) batch_69ff88f192a08190acbc2c3fc98c65c8 completed May 9, 2026, 7:20 p.m.
Created at: April 10, 2026, 4:47 a.m.