Triple

T16589320
Position Surface form Disambiguated ID Type / Status
Subject Pune Metropolitan Region E403039 entity
Predicate containsITCluster P15476 FINISHED
Object Baner E1218773 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: Baner | Statement: [Pune Metropolitan Region, containsITCluster, Baner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baner
Context triple: [Pune Metropolitan Region, containsITCluster, Baner]
  • A. Baner chosen
    Baner is a rapidly developing residential and commercial suburb in the western part of Pune, Maharashtra, known for its IT offices, eateries, and proximity to major tech hubs.
  • B. Bangar
    Bangar is a coastal municipality in the province of La Union in the Philippines, known for its handwoven textiles and agricultural products.
  • C. Shingora
    Shingora is a film featuring Indian actress and model Persis Khambatta, known for her distinctive screen presence and international appeal.
  • D. Banshiwala
    Banshiwala is a Bengali novel by acclaimed writer Shirshendu Mukhopadhyay, known for its evocative storytelling and exploration of human relationships.
  • E. Balwa
    Balwa is a municipality-level city located in Nepal's Madhesh Province.
  • 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_69d88387363c8190a97a0c942130de97 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3599f3d18819082b3e6eef5506731 completed April 18, 2026, 10:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a007599dcd4819089bbd0569b3d9a12 completed May 10, 2026, 12:10 p.m.
Created at: April 10, 2026, 5:16 a.m.