Triple

T12343854
Position Surface form Disambiguated ID Type / Status
Subject Udaipur City railway station E294297 entity
Predicate stationCode P1289 FINISHED
Object UDZ
UDZ is the station code for Udaipur City railway station, a major rail hub serving the city of Udaipur in Rajasthan, India.
 E978890 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: UDZ | Statement: [Udaipur City railway station, stationCode, UDZ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UDZ
Context triple: [Udaipur City railway station, stationCode, UDZ]
  • A. UZ
    UZ is the two-letter ISO 3166-1 alpha-2 country code assigned to Uzbekistan.
  • B. Uz
    Uz is a minor biblical figure mentioned in the Book of Genesis as one of the early descendants in Abraham’s extended family line.
  • C. UZS
    UZS is the official currency code for the Uzbekistani soʻm, the national currency of Uzbekistan.
  • D. Uzh
    Uzh is a river in Eastern Europe that flows through western Ukraine and Slovakia, serving as an important waterway for the Zakarpattia region.
  • E. UzK
    UzK is the commonly used abbreviation for the University of Cologne, one of Germany’s largest and oldest universities.
  • 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: UDZ
Triple: [Udaipur City railway station, stationCode, UDZ]
Generated description
UDZ is the station code for Udaipur City railway station, a major rail hub serving the city of Udaipur in Rajasthan, India.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UDZ
Target entity description: UDZ is the station code for Udaipur City railway station, a major rail hub serving the city of Udaipur in Rajasthan, India.
  • A. UZ
    UZ is the two-letter ISO 3166-1 alpha-2 country code assigned to Uzbekistan.
  • B. Uz
    Uz is a minor biblical figure mentioned in the Book of Genesis as one of the early descendants in Abraham’s extended family line.
  • C. UZS
    UZS is the official currency code for the Uzbekistani soʻm, the national currency of Uzbekistan.
  • D. Uzh
    Uzh is a river in Eastern Europe that flows through western Ukraine and Slovakia, serving as an important waterway for the Zakarpattia region.
  • E. UzK
    UzK is the commonly used abbreviation for the University of Cologne, one of Germany’s largest and oldest universities.
  • 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_69d6ab6ccbec8190b09e2d357aa80064 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f78a970819086beec3e4da8c49e completed April 10, 2026, 6:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62aaa1d548190be065412aab70385 completed May 2, 2026, 4:47 p.m.
NEDg Description generation batch_69f62c55aacc8190a0544306825bdfab completed May 2, 2026, 4:54 p.m.
NED2 Entity disambiguation (via description) batch_69f62d51ab8081909c6f534051019dca completed May 2, 2026, 4:58 p.m.
Created at: April 8, 2026, 9:53 p.m.