Triple

T24221522
Position Surface form Disambiguated ID Type / Status
Subject Wanindu Hasaranga E601471 entity
Predicate fullName P16 FINISHED
Object Pinnaduwage Wanindu Hasaranga de Silva
Pinnaduwage Wanindu Hasaranga de Silva is a Sri Lankan international cricketer renowned as a leg-spinning all-rounder, particularly prominent in limited-overs formats.
E1623090 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: Pinnaduwage Wanindu Hasaranga de Silva | Statement: [Wanindu Hasaranga, fullName, Pinnaduwage Wanindu Hasaranga de Silva]
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: Pinnaduwage Wanindu Hasaranga de Silva
Triple: [Wanindu Hasaranga, fullName, Pinnaduwage Wanindu Hasaranga de Silva]
Generated description
Pinnaduwage Wanindu Hasaranga de Silva is a Sri Lankan international cricketer renowned as a leg-spinning all-rounder, particularly prominent in limited-overs formats.

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_69e29537ca548190b94a37ebe1977caf completed April 17, 2026, 8:16 p.m.
NER Named-entity recognition batch_69f287d9cb4481909a77616dc123d16b completed April 29, 2026, 10:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fbd2353cc81908b1c69c5f1f57dc8 completed May 22, 2026, 2:19 a.m.
NEDg Description generation batch_6a0fbd9cd4b08190a8191001ca5d2b6f completed May 22, 2026, 2:21 a.m.
NED2 Entity disambiguation (via description) batch_6a0fbe0f87fc8190afddc29089373c2f completed May 22, 2026, 2:23 a.m.
Created at: April 17, 2026, 11:59 p.m.