Triple

T26747582

Position	Surface form	Disambiguated ID	Type / Status
Subject	Betty Boop	`E674441`	entity
Predicate	debutStudioSeries	`P27678`	FINISHED
Object	Talkartoons Talkartoons was a series of early 1930s animated short films produced by Fleischer Studios that introduced and popularized the character Betty Boop.	`E1738841`	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: Talkartoons | Statement: [Betty Boop, debutStudioSeries, Talkartoons]

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: Talkartoons
Triple: [Betty Boop, debutStudioSeries, Talkartoons]

Generated description

Talkartoons was a series of early 1930s animated short films produced by Fleischer Studios that introduced and popularized the character Betty Boop.

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

Target predicate: debutStudioSeries
Context triple: [Betty Boop, debutStudioSeries, Talkartoons]

A. debutFeatureOf
Indicates that one entity is the first major or initial feature (such as a debut work or appearance) associated with another entity.
B. debutAs
Indicates that an entity makes its first public appearance or introduction in a particular role, medium, or context.
C. debutNetworkAirDate
Indicates the calendar date on which a work was first broadcast on a television or radio network.
D. bookSeriesDebut
Indicates the work in which a particular book series first appeared or was initially introduced.
E. seriesDebut chosen
Indicates the first appearance or initial release of a series in which the subject entity is introduced.
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_69eecda63a3881908095c47900692e65`	completed	April 27, 2026, 2:44 a.m.
NER	Named-entity recognition	`batch_69f64dbbaefc8190952b8320bf4397d8`	completed	May 2, 2026, 7:17 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a11feacbeb08190aee260429d9f30d3`	completed	May 23, 2026, 7:23 p.m.
NEDg	Description generation	`batch_6a11ff7b88748190a04a8a92c016eec7`	completed	May 23, 2026, 7:26 p.m.
NED2	Entity disambiguation (via description)	`batch_6a120048ef6c8190bf4467e0742a0421`	completed	May 23, 2026, 7:30 p.m.
PD	Predicate disambiguation	`batch_69f64cacd2c08190aed8a1761d0da679`	completed	May 2, 2026, 7:12 p.m.

Created at: April 27, 2026, 3:52 a.m.