Triple

T18837214
Position Surface form Disambiguated ID Type / Status
Subject Wagdi E460694 entity
Predicate hasAlternativeName P39 FINISHED
Object Vagdi
Vagdi is an Indo-Aryan language spoken primarily in the southern part of Rajasthan, India.
 E1345544 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: Vagdi | Statement: [Wagdi, hasAlternativeName, Vagdi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vagdi
Context triple: [Wagdi, hasAlternativeName, Vagdi]
  • A. Vagra
    Vagra is a small town in the Bharuch district of Gujarat, India, known primarily as a local administrative and agricultural center.
  • B. Vingrau
    Vingrau is a small commune in southern France’s Pyrénées-Orientales department, known for its wine production and scenic location amid rugged limestone hills.
  • C. Bavadra
    Bavadra is a Fijian surname most notably associated with Timoci Bavadra, a former Prime Minister of Fiji.
  • D. Vishkanya
    Vishkanya is a 1991 Indian Hindi-language horror film known for its supernatural revenge plot and early appearance of actress Riya Sen.
  • E. Vajna
    Vajna is the surname of Andrew G. Vajna, a prominent Hungarian-American film producer known for co-founding Carolco Pictures and producing major action films such as the Rambo series.
  • 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: Vagdi
Triple: [Wagdi, hasAlternativeName, Vagdi]
Generated description
Vagdi is an Indo-Aryan language spoken primarily in the southern part of Rajasthan, India.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vagdi
Target entity description: Vagdi is an Indo-Aryan language spoken primarily in the southern part of Rajasthan, India.
  • A. Vagra
    Vagra is a small town in the Bharuch district of Gujarat, India, known primarily as a local administrative and agricultural center.
  • B. Vingrau
    Vingrau is a small commune in southern France’s Pyrénées-Orientales department, known for its wine production and scenic location amid rugged limestone hills.
  • C. Bavadra
    Bavadra is a Fijian surname most notably associated with Timoci Bavadra, a former Prime Minister of Fiji.
  • D. Vishkanya
    Vishkanya is a 1991 Indian Hindi-language horror film known for its supernatural revenge plot and early appearance of actress Riya Sen.
  • E. Vajna
    Vajna is the surname of Andrew G. Vajna, a prominent Hungarian-American film producer known for co-founding Carolco Pictures and producing major action films such as the Rambo series.
  • 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_69d8dcfa11e4819090ab1ef5bdcd2b2e completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5a99e86388190957acaaab401b5cb completed April 20, 2026, 4:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a05676b320481909bea3533d2c7fc27 completed May 14, 2026, 6:10 a.m.
NEDg Description generation batch_6a0568910c20819093ab2c08b79698cf completed May 14, 2026, 6:15 a.m.
NED2 Entity disambiguation (via description) batch_6a056959a154819095fec2ee55e4734e completed May 14, 2026, 6:19 a.m.
Created at: April 10, 2026, 11:56 a.m.