Triple

T35659857
Position Surface form Disambiguated ID Type / Status
Subject Frank O’Farrell E1030397 entity
Predicate fullName P16 FINISHED
Object Francis O’Farrell
Francis O’Farrell was an Irish footballer and manager best known for managing Manchester United in the early 1970s.
E2154253 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: Francis O’Farrell | Statement: [Frank O’Farrell, fullName, Francis O’Farrell]
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: Francis O’Farrell
Triple: [Frank O’Farrell, fullName, Francis O’Farrell]
Generated description
Francis O’Farrell was an Irish footballer and manager best known for managing Manchester United in the early 1970s.

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_69f76e09f87881909c954aaac176c34f completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79f7aa7b88190a52ff8ef9ceddf54 completed May 3, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3885e12fa481909f59f3265f2cc1eb completed June 22, 2026, 12:46 a.m.
NEDg Description generation batch_6a3886c807fc81908b54dc825e1770a6 completed June 22, 2026, 12:50 a.m.
NED2 Entity disambiguation (via description) batch_6a388786698c8190a77c02a874d0d790 completed June 22, 2026, 12:53 a.m.
Created at: May 3, 2026, 4:05 p.m.