Triple

T26411442
Position Surface form Disambiguated ID Type / Status
Subject Belgaum E663970 entity
Predicate hasLandmark P105 FINISHED
Object Kittur Rani Chennamma Circle
Kittur Rani Chennamma Circle is a prominent traffic junction and public landmark in Belgaum named in honor of the freedom fighter Rani Chennamma of Kittur.
E1725438 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: Kittur Rani Chennamma Circle | Statement: [Belgaum, hasLandmark, Kittur Rani Chennamma Circle]
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: Kittur Rani Chennamma Circle
Triple: [Belgaum, hasLandmark, Kittur Rani Chennamma Circle]
Generated description
Kittur Rani Chennamma Circle is a prominent traffic junction and public landmark in Belgaum named in honor of the freedom fighter Rani Chennamma of Kittur.

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_69ee883931888190901be96d75ee23cc completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f6113143f481909c64dfc1975e3a59 completed May 2, 2026, 2:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11aebc01b481908c4cf12e4c6efd8e completed May 23, 2026, 1:42 p.m.
NEDg Description generation batch_6a11b01df9348190a991161aa1fb8018 completed May 23, 2026, 1:48 p.m.
NED2 Entity disambiguation (via description) batch_6a11b1230c148190931c49c9df40caa4 completed May 23, 2026, 1:52 p.m.
Created at: April 26, 2026, 11:38 p.m.