Triple

T30563368
Position Surface form Disambiguated ID Type / Status
Subject Halmstads BK E777905 entity
Predicate notableFormerPlayer P304 FINISHED
Object Mikael Svensson
Mikael Svensson is a Swedish former professional footballer best known as a defender who played for clubs including Halmstads BK and Southampton FC, as well as representing Sweden internationally.
E2071084 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: Mikael Svensson | Statement: [Halmstads BK, notableFormerPlayer, Mikael Svensson]
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: Mikael Svensson
Triple: [Halmstads BK, notableFormerPlayer, Mikael Svensson]
Generated description
Mikael Svensson is a Swedish former professional footballer best known as a defender who played for clubs including Halmstads BK and Southampton FC, as well as representing Sweden internationally.

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_69f2249ed41c8190b175170ecfd6e1c5 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6890ca61481908c1d77c618321fd0 completed May 2, 2026, 11:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3675f1bddc81909cdf39baccf85bfd completed June 20, 2026, 11:13 a.m.
NEDg Description generation batch_6a367705f3d081909cbb6740ebf20535 completed June 20, 2026, 11:18 a.m.
NED2 Entity disambiguation (via description) batch_6a36776a62848190ae95f5ba56ea5e43 completed June 20, 2026, 11:20 a.m.
Created at: April 29, 2026, 8:21 p.m.