Triple

T23771180
Position Surface form Disambiguated ID Type / Status
Subject Eurovision Song Contest 2007 E587529 entity
Predicate hostCountryPerformer P46352 FINISHED
Object Hanna Pakarinen
Hanna Pakarinen is a Finnish pop-rock singer and former Finnish Idols winner who represented Finland at the Eurovision Song Contest in 2007.
E1604456 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: Hanna Pakarinen | Statement: [Eurovision Song Contest 2007, hostCountryPerformer, Hanna Pakarinen]
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: Hanna Pakarinen
Triple: [Eurovision Song Contest 2007, hostCountryPerformer, Hanna Pakarinen]
Generated description
Hanna Pakarinen is a Finnish pop-rock singer and former Finnish Idols winner who represented Finland at the Eurovision Song Contest in 2007.

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_69e2490d245881909028226a1393d624 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1c466d21c8190b45aa7a1d61a83be completed April 29, 2026, 8:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f69723b108190ae2a9b419571c58e completed May 21, 2026, 8:22 p.m.
NEDg Description generation batch_6a0f6d89d3848190ae7b29bec456cc68 completed May 21, 2026, 8:39 p.m.
NED2 Entity disambiguation (via description) batch_6a0f6e22305081909ad33dfaf65f004e completed May 21, 2026, 8:42 p.m.
Created at: April 17, 2026, 7:15 p.m.