Triple

T35403240
Position Surface form Disambiguated ID Type / Status
Subject Carousel (1994 revival) E1023291 entity
Predicate featuredActor P5563 FINISHED
Object Eddie Korbich
Eddie Korbich is an American stage actor and singer known for his work in Broadway musicals and revivals.
E2151480 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: Eddie Korbich | Statement: [Carousel (1994 revival), featuredActor, Eddie Korbich]
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: Eddie Korbich
Triple: [Carousel (1994 revival), featuredActor, Eddie Korbich]
Generated description
Eddie Korbich is an American stage actor and singer known for his work in Broadway musicals and revivals.

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_69f76df43ca4819098711ca4370f1bb9 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7953da17c8190a0a038341f387831 completed May 3, 2026, 6:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38726acd808190902b60b419f19dae completed June 21, 2026, 11:23 p.m.
NEDg Description generation batch_6a3874101e2081908309ddb21529e625 completed June 21, 2026, 11:30 p.m.
NED2 Entity disambiguation (via description) batch_6a3874b34a448190bf6649ec96e454cc completed June 21, 2026, 11:33 p.m.
Created at: May 3, 2026, 4:03 p.m.