Triple

T28801037
Position Surface form Disambiguated ID Type / Status
Subject Terje Hauge E727234 entity
Predicate leagueRefereed P36702 FINISHED
Object Norwegian Premier League
The Norwegian Premier League is the top professional football division in Norway, featuring the country’s leading clubs competing for the national championship.
E1445482 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: Norwegian Premier League | Statement: [Terje Hauge, leagueRefereed, Norwegian Premier League]
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: Norwegian Premier League
Triple: [Terje Hauge, leagueRefereed, Norwegian Premier League]
Generated description
The Norwegian Premier League is the top professional football division in Norway, featuring the country’s leading clubs competing for the national championship.

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_69f0319b7c44819085736bcc256185e6 completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f658aa9fa88190818544cbf3049619 completed May 2, 2026, 8:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24a279aa908190b9334c9215ec2093 completed June 6, 2026, 10:43 p.m.
NEDg Description generation batch_6a24a695a9988190bd815507f8027193 completed June 6, 2026, 11 p.m.
NED2 Entity disambiguation (via description) batch_6a24aab9053081909350507082946a76 completed June 6, 2026, 11:18 p.m.
Created at: April 28, 2026, 6:27 a.m.