Triple

T20568895
Position Surface form Disambiguated ID Type / Status
Subject Ujjain Junction E505037 entity
Predicate stationCode P1289 FINISHED
Object UJN
UJN is the station code for Ujjain Junction, a major railway station serving the historic city of Ujjain in Madhya Pradesh, India.
 E1437975 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: UJN | Statement: [Ujjain Junction, stationCode, UJN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UJN
Context triple: [Ujjain Junction, stationCode, UJN]
  • A. UJN
    UJN is the commonly used abbreviation for the University of Jinan, a comprehensive higher education institution located in Jinan, China.
  • B. UJ
    UJ is a major public university in Johannesburg, South Africa, known for its diverse academic programs and strong focus on research and innovation.
  • C. JU
    JU is the two-letter IATA airline designator assigned to Air Serbia, the national flag carrier of Serbia.
  • D. JU
    JU is the commonly used abbreviation for Jiwaji University, a public university located in Gwalior, Madhya Pradesh, India.
  • E. JU
    JU is the station code for Jodhpur Junction, a major railway hub in the Indian state of Rajasthan.
  • 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: UJN
Triple: [Ujjain Junction, stationCode, UJN]
Generated description
UJN is the station code for Ujjain Junction, a major railway station serving the historic city of Ujjain in Madhya Pradesh, India.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UJN
Target entity description: UJN is the station code for Ujjain Junction, a major railway station serving the historic city of Ujjain in Madhya Pradesh, India.
  • A. UJN
    UJN is the commonly used abbreviation for the University of Jinan, a comprehensive higher education institution located in Jinan, China.
  • B. UJ
    UJ is a major public university in Johannesburg, South Africa, known for its diverse academic programs and strong focus on research and innovation.
  • C. JU
    JU is the two-letter IATA airline designator assigned to Air Serbia, the national flag carrier of Serbia.
  • D. JU
    JU is the commonly used abbreviation for Jiwaji University, a public university located in Gwalior, Madhya Pradesh, India.
  • E. JU
    JU is the station code for Jodhpur Junction, a major railway hub in the Indian state of Rajasthan.
  • 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_69e0b4b721588190993ac7b0a9be2736 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a7a4b90c81909854dac72f671eec completed April 20, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08ace1b0288190a7e68ad0e83e11b6 completed May 16, 2026, 5:44 p.m.
NEDg Description generation batch_6a08ad7f0cac81908bd2aa0cafe95b15 completed May 16, 2026, 5:46 p.m.
NED2 Entity disambiguation (via description) batch_6a08adeae6d881909b19929e0e5aa1c9 completed May 16, 2026, 5:48 p.m.
Created at: April 16, 2026, 11:39 a.m.