Triple

T34795353

Position	Surface form	Disambiguated ID	Type / Status
Subject	R v Penguin Books Ltd	`E1003061`	entity
Predicate	defenceCounsel	`P60566`	FINISHED
Object	Gerald Gardiner Gerald Gardiner was a prominent British barrister and Labour politician who served as Lord Chancellor and played a key role in legal reform in the mid-20th century United Kingdom.	`E2113193`	NE FINISHED

How this triple was built (3 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: Gerald Gardiner | Statement: [R v Penguin Books Ltd, defenceCounsel, Gerald Gardiner]

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: Gerald Gardiner
Triple: [R v Penguin Books Ltd, defenceCounsel, Gerald Gardiner]

Generated description

Gerald Gardiner was a prominent British barrister and Labour politician who served as Lord Chancellor and played a key role in legal reform in the mid-20th century United Kingdom.

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: defenceCounsel
Context triple: [R v Penguin Books Ltd, defenceCounsel, Gerald Gardiner]

A. defenseLawyer chosen
Indicates that one entity serves as the legal representative defending another entity in a legal proceeding or case.
B. defendant
Indicates that an entity is the party accused or sued in a legal action or proceeding.
C. hasDefenseCounsel
Indicates that a person or party is represented or assisted by a defense attorney or legal counsel in a legal matter.
D. coDefendant
Indicates that two or more parties are jointly named and involved as defendants in the same legal case or proceeding.
E. counselForProsecution
Indicates that an entity serves as a legal representative or advisor acting on behalf of the prosecution in a legal proceeding.
F. None of above.

Provenance (6 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_69f76db543808190b188c6c86a91491b`	completed	May 3, 2026, 3:45 p.m.
NER	Named-entity recognition	`batch_69f78c61ed4c8190ad84c918fa9af55a`	completed	May 3, 2026, 5:56 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a376fa822e8819099400198c9b6d5a5`	completed	June 21, 2026, 4:59 a.m.
NEDg	Description generation	`batch_6a37703823ac81908261228f65fcfa4b`	completed	June 21, 2026, 5:01 a.m.
NED2	Entity disambiguation (via description)	`batch_6a37716ab2c48190b7c24792201885c8`	completed	June 21, 2026, 5:06 a.m.
PD	Predicate disambiguation	`batch_69f78b8cb3a881909ebaac1b503988c2`	completed	May 3, 2026, 5:53 p.m.

Created at: May 3, 2026, 3:59 p.m.