Triple

T34680647
Position Surface form Disambiguated ID Type / Status
Subject The Oval E890611 entity
Predicate leadActor P1507 FINISHED
Object Lodric D. Collins
Lodric D. Collins is an American actor best known for his prominent role on Tyler Perry’s primetime drama series "The Oval."
E2114324 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: Lodric D. Collins | Statement: [The Oval, leadActor, Lodric D. Collins]
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: Lodric D. Collins
Triple: [The Oval, leadActor, Lodric D. Collins]
Generated description
Lodric D. Collins is an American actor best known for his prominent role on Tyler Perry’s primetime drama series "The Oval."

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_69f349dabc008190a18999c26682ed47 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f723282ac48190855661f3023221db completed May 3, 2026, 10:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a376f91d5f08190b15493b9d6819a8b completed June 21, 2026, 4:58 a.m.
NEDg Description generation batch_6a3773ae72608190984873c9fffdee39 completed June 21, 2026, 5:16 a.m.
NED2 Entity disambiguation (via description) batch_6a3773ff7b1481909b4d3589ad547e68 completed June 21, 2026, 5:17 a.m.
Created at: May 1, 2026, 2:05 a.m.