Triple

T25195226
Position Surface form Disambiguated ID Type / Status
Subject Denny Duquette E630981 entity
Predicate firstAppearanceEpisode P16444 FINISHED
Object “Begin the Begin”
“Begin the Begin” is an early episode of the medical drama Grey’s Anatomy that introduces the character Denny Duquette, a heart patient who becomes central to a major romantic and emotional storyline.
E1666760 NE FINISHED

How this triple was built (2 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: “Begin the Begin” | Statement: [Denny Duquette, firstAppearanceEpisode, “Begin the Begin”]
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: “Begin the Begin”
Triple: [Denny Duquette, firstAppearanceEpisode, “Begin the Begin”]
Generated description
“Begin the Begin” is an early episode of the medical drama Grey’s Anatomy that introduces the character Denny Duquette, a heart patient who becomes central to a major romantic and emotional storyline.

Provenance (5 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_69e75a8a6d088190ba1e82a4345225e7 completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f46e12ea808190b08610a16810bc3a completed May 1, 2026, 9:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105d2882788190824154d643158457 completed May 22, 2026, 1:42 p.m.
NEDg Description generation batch_6a105e17b4708190bceee2e6c3f4f3a7 completed May 22, 2026, 1:45 p.m.
NED2 Entity disambiguation (via description) batch_6a105fa4a3a48190a9c0faa1e90d9102 completed May 22, 2026, 1:52 p.m.
Created at: April 21, 2026, 12:46 p.m.