Triple

T33556164

Position	Surface form	Disambiguated ID	Type / Status
Subject	Our Game	`E859479`	entity
Predicate	hasProtégéCharacter	`P51551`	FINISHED
Object	Larry Pettifer Larry Pettifer is a fictional British academic and double agent in John le Carré’s espionage novel "Our Game," whose divided loyalties drive much of the story’s intrigue.	`E2066088`	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: Larry Pettifer | Statement: [Our Game, hasProtégéCharacter, Larry Pettifer]

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: Larry Pettifer
Triple: [Our Game, hasProtégéCharacter, Larry Pettifer]

Generated description

Larry Pettifer is a fictional British academic and double agent in John le Carré’s espionage novel "Our Game," whose divided loyalties drive much of the story’s intrigue.

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

Target predicate: hasProtégéCharacter
Context triple: [Our Game, hasProtégéCharacter, Larry Pettifer]

A. protégéPlayedBy
Indicates that the protégé character is portrayed or acted by a particular performer or actor.
B. propertyOnCharacters
Indicates that a certain property or attribute is associated with one or more characters.
C. protégéOf chosen
Indicates that one entity is mentored, trained, or guided in their development by another, more experienced entity.
D. hasHumanCharacterRole
Indicates that an entity is assigned a role or function specifically associated with a human character within a context such as a story, performance, or representation.
E. subjectHasCharacteristic
Indicates that a subject possesses, exhibits, or is defined by a particular characteristic or attribute.
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_69f3497b2b68819093207971b5e13dc8`	completed	April 30, 2026, 12:22 p.m.
NER	Named-entity recognition	`batch_6a01a534a8908190aa888d6be5deb824`	completed	May 11, 2026, 9:45 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a365c6174d88190beadd8b6fc396927`	completed	June 20, 2026, 9:24 a.m.
NEDg	Description generation	`batch_6a365d2c51808190aa3437c2aa4af4d0`	completed	June 20, 2026, 9:28 a.m.
NED2	Entity disambiguation (via description)	`batch_6a365de322208190b3fc9539d7a2b18b`	completed	June 20, 2026, 9:31 a.m.
PD	Predicate disambiguation	`batch_6a01a507c1f081909ff6abc5575db0bb`	completed	May 11, 2026, 9:44 a.m.

Created at: May 1, 2026, 1:40 a.m.