Triple

T36380159
Position Surface form Disambiguated ID Type / Status
Subject ICC Cricket World Cup Qualifier 2023 matches E896022 entity
Predicate notableVenue P373 FINISHED
Object Takashinga Sports Club
Takashinga Sports Club is a prominent cricket ground in Harare, Zimbabwe, known for hosting international and high-profile limited-overs matches.
E2184617 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: Takashinga Sports Club | Statement: [ICC Cricket World Cup Qualifier 2023 matches, notableVenue, Takashinga Sports Club]
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: Takashinga Sports Club
Triple: [ICC Cricket World Cup Qualifier 2023 matches, notableVenue, Takashinga Sports Club]
Generated description
Takashinga Sports Club is a prominent cricket ground in Harare, Zimbabwe, known for hosting international and high-profile limited-overs matches.

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_69f76e51d358819092bbc5f119f49476 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bb1a48e08190a6bb0096ad637cf3 completed May 3, 2026, 9:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39c3fbee7c8190998059ce8c0f3985 completed June 22, 2026, 11:23 p.m.
NEDg Description generation batch_6a39c5ba1a5c8190827e09d608eac04f completed June 22, 2026, 11:31 p.m.
NED2 Entity disambiguation (via description) batch_6a39c9af2e6481909469e1fb9d3de72a completed June 22, 2026, 11:47 p.m.
Created at: May 3, 2026, 4:10 p.m.