Triple

T32606368

Position	Surface form	Disambiguated ID	Type / Status
Subject	Saratoga (1937 film)	`E833531`	entity
Predicate	leadCharacterPlayedByClarkGable	`P174932`	FINISHED
Object	Duke Bradley Duke Bradley is the charismatic gambler and main male protagonist portrayed by Clark Gable in the 1937 romantic comedy film "Saratoga."	`E2015133`	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: Duke Bradley | Statement: [Saratoga (1937 film), leadCharacterPlayedByClarkGable, Duke Bradley]

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: Duke Bradley
Triple: [Saratoga (1937 film), leadCharacterPlayedByClarkGable, Duke Bradley]

Generated description

Duke Bradley is the charismatic gambler and main male protagonist portrayed by Clark Gable in the 1937 romantic comedy film "Saratoga."

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

Target predicate: leadCharacterPlayedByClarkGable
Context triple: [Saratoga (1937 film), leadCharacterPlayedByClarkGable, Duke Bradley]

A. humphreyBogartRole
Indicates that one entity is a role or character portrayed by Humphrey Bogart in a film, play, or other performance.
B. hasGingerRogersRole
Indicates that an entity is assigned or associated with a role specifically identified as the "Ginger Rogers" role in a given context or production.
C. portrayedIn1953FilmBy
Indicates that an entity (typically a person or character) was depicted or played by another entity in a film released in the year 1953.
D. hasGlennFordRole
Indicates that an entity has a role played by the actor Glenn Ford.
E. AvaGardnerRole
Indicates that an entity represents a role or character portrayed by Ava Gardner in a film, television production, or other performance.
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_69f3492bfa648190b6ae472074634e29`	completed	April 30, 2026, 12:21 p.m.
NER	Named-entity recognition	`batch_69f6c90790788190a1ed09adc86ed22d`	completed	May 3, 2026, 4:03 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a34861488348190bb57fcd0b3443685`	completed	June 18, 2026, 11:58 p.m.
NEDg	Description generation	`batch_6a34892fb44c819086687de35e99b882`	completed	June 19, 2026, 12:11 a.m.
NED2	Entity disambiguation (via description)	`batch_6a34899e7afc8190bfda3571653a9f05`	completed	June 19, 2026, 12:13 a.m.
PD	Predicate disambiguation	`batch_69f6c3f42fbc8190a06eb1044c9e6094`	completed	May 3, 2026, 3:41 a.m.
PDg	Predicate description generation	`batch_69f6c814c26c81908f5c47285129ff2a`	completed	May 3, 2026, 3:59 a.m.

Created at: May 1, 2026, 1:05 a.m.