Triple

T35432649

Position	Surface form	Disambiguated ID	Type / Status
Subject	The Arrangement	`E1024104`	entity
Predicate	characterPlayedByAutumnReeser	`P200627`	FINISHED
Object	Leslie Bellcamp Leslie Bellcamp is a fictional character from the television series "The Arrangement," portrayed as a driven and image-conscious Hollywood publicist navigating the darker side of the entertainment industry.	`E2140314`	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: Leslie Bellcamp | Statement: [The Arrangement, characterPlayedByAutumnReeser, Leslie Bellcamp]

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: Leslie Bellcamp
Triple: [The Arrangement, characterPlayedByAutumnReeser, Leslie Bellcamp]

Generated description

Leslie Bellcamp is a fictional character from the television series "The Arrangement," portrayed as a driven and image-conscious Hollywood publicist navigating the darker side of the entertainment industry.

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

Target predicate: characterPlayedByAutumnReeser
Context triple: [The Arrangement, characterPlayedByAutumnReeser, Leslie Bellcamp]

A. characterPlayedBy Larisa Oleynik
Indicates that a specific fictional character is portrayed or acted by Larisa Oleynik.
B. characterPlayedBy Emmanuelle Chriqui
Indicates that the role or character in question is portrayed or acted by Emmanuelle Chriqui.
C. characterPlayedByAlexandraShipp
Indicates that a given character is portrayed or acted by Alexandra Shipp.
D. characterPortrayedByCheyenneJackson
Indicates that a given character is portrayed or played by the actor Cheyenne Jackson.
E. characterPlayedBy_MichelleRyan
Indicates that the subject is a character portrayed or played by Michelle Ryan.
F. None of above. chosen

Provenance (7 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_69f76df743c48190aecb6dd79efb0d95`	completed	May 3, 2026, 3:47 p.m.
NER	Named-entity recognition	`batch_69ff9bed58dc8190a204816d4ed6c32c`	completed	May 9, 2026, 8:41 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a3836bcde308190b5ab6438f2e65445`	completed	June 21, 2026, 7:08 p.m.
NEDg	Description generation	`batch_6a383817ee348190af59b2a3b11cf608`	completed	June 21, 2026, 7:14 p.m.
NED2	Entity disambiguation (via description)	`batch_6a383916e7ec81909b37a77bd6b0e2ed`	completed	June 21, 2026, 7:18 p.m.
PD	Predicate disambiguation	`batch_69ff9b69653c81908ab0d88055a66a88`	completed	May 9, 2026, 8:39 p.m.
PDg	Predicate description generation	`batch_69ff9bec9d748190869caebf6bf0c78f`	completed	May 9, 2026, 8:41 p.m.

Created at: May 3, 2026, 4:03 p.m.