Triple

T27068951
Position Surface form Disambiguated ID Type / Status
Subject Reykjavík metropolitan area E685260 entity
Predicate hasSportsTeam P330 FINISHED
Object FH Hafnarfjörður
FH Hafnarfjörður is a prominent Icelandic multi-sport club best known for its successful football team based in the town of Hafnarfjörður near Reykjavík.
E1755391 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: FH Hafnarfjörður | Statement: [Reykjavík metropolitan area, hasSportsTeam, FH Hafnarfjörður]
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: FH Hafnarfjörður
Triple: [Reykjavík metropolitan area, hasSportsTeam, FH Hafnarfjörður]
Generated description
FH Hafnarfjörður is a prominent Icelandic multi-sport club best known for its successful football team based in the town of Hafnarfjörður near Reykjavík.

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_69ef14835fcc81908bd737b4267ae528 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f622eb05c08190af8651dda80ace28 completed May 2, 2026, 4:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a123ad803688190bb579cd9339576bb completed May 23, 2026, 11:40 p.m.
NEDg Description generation batch_6a123c27062881908664273fcb5ea8b8 completed May 23, 2026, 11:45 p.m.
NED2 Entity disambiguation (via description) batch_6a123cea536c81908bfb43ef2224a964 completed May 23, 2026, 11:48 p.m.
Created at: April 27, 2026, 8:26 a.m.