Triple

T25339580

Position	Surface form	Disambiguated ID	Type / Status
Subject	To Have and to Hold (1916 film)	`E635371`	entity
Predicate	mainCharacterFromSourceWork	`P146684`	FINISHED
Object	Lady Jocelyn Leigh Lady Jocelyn Leigh is the noblewoman heroine of Mary Johnston’s historical romance "To Have and to Hold," whose perilous journey and complex marriage in colonial Virginia drive the story’s central drama.	`E1675667`	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: Lady Jocelyn Leigh | Statement: [To Have and to Hold (1916 film), mainCharacterFromSourceWork, Lady Jocelyn Leigh]

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: Lady Jocelyn Leigh
Triple: [To Have and to Hold (1916 film), mainCharacterFromSourceWork, Lady Jocelyn Leigh]

Generated description

Lady Jocelyn Leigh is the noblewoman heroine of Mary Johnston’s historical romance "To Have and to Hold," whose perilous journey and complex marriage in colonial Virginia drive the story’s central drama.

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

Target predicate: mainCharacterFromSourceWork
Context triple: [To Have and to Hold (1916 film), mainCharacterFromSourceWork, Lady Jocelyn Leigh]

A. basedOnCharacterFromWork
Indicates that one entity is derived from, inspired by, or modeled after a character that appears in another creative work.
B. hasProtagonistFromSource
Indicates that a work’s main character originates from, or is derived from, a specified source (such as another work, franchise, or medium).
C. narrativeSourceCharacter
Indicates that a particular character serves as the source or narrator from whose perspective the narrative is presented.
D. hasMainCharacterFrom chosen
Indicates that a work of fiction has a main character who originates from or belongs to a specified place, group, or source.
E. mainCharacterCodeNumber
Indicates that an entity is identified as the primary or central character by a specific code number.
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_69e75a99bd6481909476115b35b9a8e4`	completed	April 21, 2026, 11:08 a.m.
NER	Named-entity recognition	`batch_69f60c3b09488190ade1b69ff7f0df0e`	completed	May 2, 2026, 2:37 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a1075f4e0dc8190ba2e0d68b99a5d21`	completed	May 22, 2026, 3:27 p.m.
NEDg	Description generation	`batch_6a107730a4ec8190a1f21393c94ab732`	completed	May 22, 2026, 3:33 p.m.
NED2	Entity disambiguation (via description)	`batch_6a1077e5ab8c8190b7e81764d7aacc72`	completed	May 22, 2026, 3:36 p.m.
PD	Predicate disambiguation	`batch_69f60b8461ac81908c5bd3d73eed59f4`	completed	May 2, 2026, 2:34 p.m.

Created at: April 21, 2026, 1:32 p.m.