Triple

T33265092

Position	Surface form	Disambiguated ID	Type / Status
Subject	Borachio	`E851621`	entity
Predicate	feignsCourtshipOf	`P139538`	FINISHED
Object	Margaret Margaret is a character in Shakespeare's play "Much Ado About Nothing," a waiting gentlewoman to Hero who becomes unwittingly involved in Don John's plot through Borachio's deception.	`E851029`	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: Margaret | Statement: [Borachio, feignsCourtshipOf, Margaret]

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: Margaret
Triple: [Borachio, feignsCourtshipOf, Margaret]

Generated description

Margaret is a character in Shakespeare's play "Much Ado About Nothing," a waiting gentlewoman to Hero who becomes unwittingly involved in Don John's plot through Borachio's deception.

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

Target predicate: feignsCourtshipOf
Context triple: [Borachio, feignsCourtshipOf, Margaret]

A. courtshipMode
Indicates the manner or strategy by which one entity engages in behaviors intended to attract or win the favor of another for a romantic or reproductive relationship.
B. notableDeviceInCourtship
Indicates that a particular device plays a significant or characteristic role in the courtship behavior or ritual between entities.
C. courtships chosen
Indicates that one entity engages in courtship behavior toward another, typically as part of initiating or maintaining a romantic or mating relationship.
D. needsBestMan
Indicates that one entity requires or is seeking another entity to serve as their best man in a wedding or similar ceremony.
E. servesAtThePleasureOf
Indicates that one entity holds a position or role that can be terminated at any time by another entity, typically at the discretion or will of that other entity.
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_69f349642dac81908a37ffcc3b976a55`	completed	April 30, 2026, 12:21 p.m.
NER	Named-entity recognition	`batch_69f6e02ba6b881908dfafc52d3b75f1c`	completed	May 3, 2026, 5:42 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a35431412408190a2a16f174b43f6df`	completed	June 19, 2026, 1:24 p.m.
NEDg	Description generation	`batch_6a3544112e5c81909b7f1aa7fc559640`	completed	June 19, 2026, 1:28 p.m.
NED2	Entity disambiguation (via description)	`batch_6a3548ae60f48190801d64acb5762591`	completed	June 19, 2026, 1:48 p.m.
PD	Predicate disambiguation	`batch_69f6de09c2f481909f8b2545d3208c9f`	completed	May 3, 2026, 5:32 a.m.

Created at: May 1, 2026, 1:32 a.m.