Triple

T35965823

Position	Surface form	Disambiguated ID	Type / Status
Subject	Morgan York	`E1040138`	entity
Predicate	sharesSubjectMatterWith	`P76081`	FINISHED
Object	Disney Channel original programming Disney Channel original programming consists of the network’s in-house produced television series and movies aimed primarily at children and preteens, often featuring family-friendly comedy, drama, and fantasy themes.	`E683454`	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: Disney Channel original programming | Statement: [Morgan York, sharesSubjectMatterWith, Disney Channel original programming]

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: Disney Channel original programming
Triple: [Morgan York, sharesSubjectMatterWith, Disney Channel original programming]

Generated description

Disney Channel original programming consists of the network’s in-house produced television series and movies aimed primarily at children and preteens, often featuring family-friendly comedy, drama, and fantasy themes.

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

Target predicate: sharesSubjectMatterWith
Context triple: [Morgan York, sharesSubjectMatterWith, Disney Channel original programming]

A. sharesSubjectWith chosen
Indicates that two items are associated with or pertain to the same subject or topic.
B. sharesUniverseWith
Indicates that two entities exist within the same fictional or narrative universe, implying shared continuity, setting, or canon.
C. sharesSectionsWith
Indicates that two entities have one or more sections or segments in common.
D. sharesFieldWith
Indicates that two entities are involved in or associated with the same field, discipline, or area of specialization.
E. sharesWith
Indicates that one entity gives another entity access to or use of something it possesses.
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_69f76e26b21081909fd9ffb3aff6c77a`	completed	May 3, 2026, 3:47 p.m.
NER	Named-entity recognition	`batch_6a00781b749c8190921c46e110cae0b0`	completed	May 10, 2026, 12:20 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a38b70b76388190b28515d67e46a79e`	completed	June 22, 2026, 4:16 a.m.
NEDg	Description generation	`batch_6a38b7c2a1c08190854419e90ce71f19`	completed	June 22, 2026, 4:19 a.m.
NED2	Entity disambiguation (via description)	`batch_6a38b84d6374819094b31aa543799666`	completed	June 22, 2026, 4:21 a.m.
PD	Predicate disambiguation	`batch_6a0077df3c8481909fabc9e84f5936e3`	completed	May 10, 2026, 12:19 p.m.

Created at: May 3, 2026, 4:07 p.m.