Triple

T13592022
Position Surface form Disambiguated ID Type / Status
Subject DXN E324713 entity
Predicate alsoKnownAs P39 FINISHED
Object Jewar Airport E324712 NE FINISHED

How this triple was built (2 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: Jewar Airport | Statement: [DXN, alsoKnownAs, Jewar Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jewar Airport
Context triple: [DXN, alsoKnownAs, Jewar Airport]
  • A. Jewar Airport chosen
    Jewar Airport is a major upcoming international airport project in Uttar Pradesh, India, intended to serve the Delhi-NCR region and ease congestion at Indira Gandhi International Airport.
  • B. Naini Saini Airport
    Naini Saini Airport is a regional airport serving the town of Pithoragarh in the hilly state of Uttarakhand, India.
  • C. Maharana Pratap Airport
    Maharana Pratap Airport is the main domestic airport serving the city of Udaipur in the Indian state of Rajasthan.
  • D. Jamnagar Airport
    Jamnagar Airport is a domestic airport in Jamnagar, Gujarat, India, serving as a key regional hub for civilian flights and nearby industrial and defense facilities.
  • E. Ayodhya Airport
    Ayodhya Airport is a modern international airport serving the city of Ayodhya in Uttar Pradesh, India, developed to handle growing religious tourism and regional air traffic.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d80769eaf081909d82f44e484d6113 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb056ce088190a6feb4266633d18b completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce60b1248190addfbfc1c5ccd2d1 completed May 3, 2026, 10:38 p.m.
Created at: April 9, 2026, 9:49 p.m.