Triple

T15648224
Position Surface form Disambiguated ID Type / Status
Subject Banaskantha district E376236 entity
Predicate hasTown P847 FINISHED
Object Vav
Vav is a town located in the Banaskantha district of the Indian state of Gujarat.
E1169433 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: Vav | Statement: [Banaskantha district, hasTown, Vav]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vav
Context triple: [Banaskantha district, hasTown, Vav]
  • A. Sloup
    Sloup is a small village in the Czech Republic known as a gateway to the Moravian Karst cave region and its popular karst formations.
  • B. Vigla
    Vigla is a notable summit of Mount Pangaion in northern Greece, known for its mountainous terrain and scenic views.
  • C. Viga
    Viga is a coastal agricultural municipality on the island province of Catanduanes in the Bicol Region of the Philippines.
  • D. Pyramida
    Pyramida is the summit that forms the highest peak of Mount Giona in central Greece.
  • E. Vanakbara
    Vanakbara is a coastal village and fishing port located in the Diu district of the Indian union territory of Dadra and Nagar Haveli and Daman and Diu.
  • 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: Vav
Triple: [Banaskantha district, hasTown, Vav]
Generated description
Vav is a town located in the Banaskantha district of the Indian state of Gujarat.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vav
Target entity description: Vav is a town located in the Banaskantha district of the Indian state of Gujarat.
  • A. Sloup
    Sloup is a small village in the Czech Republic known as a gateway to the Moravian Karst cave region and its popular karst formations.
  • B. Vigla
    Vigla is a notable summit of Mount Pangaion in northern Greece, known for its mountainous terrain and scenic views.
  • C. Viga
    Viga is a coastal agricultural municipality on the island province of Catanduanes in the Bicol Region of the Philippines.
  • D. Pyramida
    Pyramida is the summit that forms the highest peak of Mount Giona in central Greece.
  • E. Vanakbara
    Vanakbara is a coastal village and fishing port located in the Diu district of the Indian union territory of Dadra and Nagar Haveli and Daman and Diu.
  • 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_69d85cd1564c8190991adda63bfab4b0 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04ed7212c8190be6ff76afa25f7ca completed April 16, 2026, 2:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff67936e388190913c9060194e5b53 completed May 9, 2026, 4:57 p.m.
NEDg Description generation batch_69ff6883b5048190b64e4361bc89dd80 completed May 9, 2026, 5:01 p.m.
NED2 Entity disambiguation (via description) batch_69ff6911a76c819088c8a86d2106b6c6 completed May 9, 2026, 5:04 p.m.
Created at: April 10, 2026, 4:15 a.m.