Triple

T36476391
Position Surface form Disambiguated ID Type / Status
Subject Hakkarainen E898678 entity
Predicate hasNotableBearer P458 FINISHED
Object Teuvo Hakkarainen
Teuvo Hakkarainen is a Finnish politician and businessman known for his tenure as a Member of Parliament representing the Finns Party and later the Blue Reform, often drawing attention for his controversial statements.
E2202411 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: Teuvo Hakkarainen | Statement: [Hakkarainen, hasNotableBearer, Teuvo Hakkarainen]
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: Teuvo Hakkarainen
Triple: [Hakkarainen, hasNotableBearer, Teuvo Hakkarainen]
Generated description
Teuvo Hakkarainen is a Finnish politician and businessman known for his tenure as a Member of Parliament representing the Finns Party and later the Blue Reform, often drawing attention for his controversial statements.

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_69f76e5a0e088190a2b6706aeb41723c completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bdd7d4d88190a6bd2146b090cc7a completed May 3, 2026, 9:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3dfabd36948190be1dbb614c07d905 completed June 26, 2026, 4:06 a.m.
NEDg Description generation batch_6a3dfe292b788190a6316cc67c5ce0bc completed June 26, 2026, 4:20 a.m.
NED2 Entity disambiguation (via description) batch_6a3e03327fe481908577744b1addfa8a completed June 26, 2026, 4:42 a.m.
Created at: May 3, 2026, 4:10 p.m.