Triple

T20130427
Position Surface form Disambiguated ID Type / Status
Subject Burhanpur railway station E490873 entity
Predicate stationCode P1289 FINISHED
Object BAU
BAU is the Indian Railways station code for Burhanpur railway station in Madhya Pradesh, India.
 E1412909 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: BAU | Statement: [Burhanpur railway station, stationCode, BAU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BAU
Context triple: [Burhanpur railway station, stationCode, BAU]
  • A. BAW
    BAW is the ICAO airline designator used in aviation to identify British Airways flights and operations.
  • B. Ba
    Ba is a town and district on the northwestern coast of Viti Levu in Fiji, known for its sugar industry and cultural diversity.
  • C. BAJ
    BAJ is the station code for Baglan railway station in Wales, United Kingdom.
  • D. BAL
    BAL is the Amtrak station code for Pennsylvania Station in Baltimore, Maryland, a major rail hub in the city’s transportation network.
  • E. BAL
    BAL is the commonly used acronym for the Basketball Africa League, a professional pan-African basketball competition organized in partnership with the NBA and FIBA.
  • 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: BAU
Triple: [Burhanpur railway station, stationCode, BAU]
Generated description
BAU is the Indian Railways station code for Burhanpur railway station in Madhya Pradesh, India.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BAU
Target entity description: BAU is the Indian Railways station code for Burhanpur railway station in Madhya Pradesh, India.
  • A. BAW
    BAW is the ICAO airline designator used in aviation to identify British Airways flights and operations.
  • B. Ba
    Ba is a town and district on the northwestern coast of Viti Levu in Fiji, known for its sugar industry and cultural diversity.
  • C. BAJ
    BAJ is the station code for Baglan railway station in Wales, United Kingdom.
  • D. BAL
    BAL is the Amtrak station code for Pennsylvania Station in Baltimore, Maryland, a major rail hub in the city’s transportation network.
  • E. BAL
    BAL is the commonly used acronym for the Basketball Africa League, a professional pan-African basketball competition organized in partnership with the NBA and FIBA.
  • 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_69da62651a0c8190a3e05e95e056a66b completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e6676183dc8190b65d0def681aaa1e completed April 20, 2026, 5:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a082dddf6388190b765f9092d2f035a completed May 16, 2026, 8:42 a.m.
NEDg Description generation batch_6a082e93a1e88190bac5daae12ece9f2 completed May 16, 2026, 8:45 a.m.
NED2 Entity disambiguation (via description) batch_6a082f334dd481908edb6ea3ae07e0a7 completed May 16, 2026, 8:47 a.m.
Created at: April 11, 2026, 11:31 p.m.