Triple

T24129272
Position Surface form Disambiguated ID Type / Status
Subject Charlie Runkle E597898 entity
Predicate spouse P13 FINISHED
Object Marcy Runkle
Marcy Runkle is a central character in the television series "Californication," known as Charlie Runkle’s sharp-tongued, strong-willed wife whose tumultuous marriage provides much of the show’s comedic and dramatic tension.
E1643129 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: Marcy Runkle | Statement: [Charlie Runkle, spouse, Marcy Runkle]
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: Marcy Runkle
Triple: [Charlie Runkle, spouse, Marcy Runkle]
Generated description
Marcy Runkle is a central character in the television series "Californication," known as Charlie Runkle’s sharp-tongued, strong-willed wife whose tumultuous marriage provides much of the show’s comedic and dramatic tension.

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_69e288c808b881909fed7d18f04bcbbe completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1df751c94819084652a89c7c2cc1f completed April 29, 2026, 10:37 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0ff83111448190b1c4fdc7af609d5c completed May 22, 2026, 6:31 a.m.
NEDg Description generation batch_6a0ff9076a7081908cd02686d3ac6080 completed May 22, 2026, 6:34 a.m.
NED2 Entity disambiguation (via description) batch_6a0ffcc3dc0c8190a4b8e0b3d68e8c0a completed May 22, 2026, 6:50 a.m.
Created at: April 17, 2026, 11:23 p.m.