Triple

T29077318
Position Surface form Disambiguated ID Type / Status
Subject Kara Wallace Clarke E735976 entity
Predicate associatedWith P37 FINISHED
Object David Clarke
David Clarke is a central character in the TV series "Revenge," known as the wrongfully convicted father whose fate drives his daughter Emily Thorne’s quest for vengeance.
E735268 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: David Clarke | Statement: [Kara Wallace Clarke, associatedWith, David Clarke]
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: David Clarke
Triple: [Kara Wallace Clarke, associatedWith, David Clarke]
Generated description
David Clarke is a central character in the TV series "Revenge," known as the wrongfully convicted father whose fate drives his daughter Emily Thorne’s quest for vengeance.

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_69f077e9b0a48190bb79548279cb7f64 completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f661407e5481908d8f224787f5f6be completed May 2, 2026, 8:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2569a4487881909205d612ed1a0c0b completed June 7, 2026, 12:52 p.m.
NEDg Description generation batch_6a256de41c4481909176bfe24f1e4fe8 completed June 7, 2026, 1:11 p.m.
NED2 Entity disambiguation (via description) batch_6a25724ed7588190862ceef339305f35 completed June 7, 2026, 1:29 p.m.
Created at: April 28, 2026, 10:23 a.m.