Triple

T29114247
Position Surface form Disambiguated ID Type / Status
Subject Eric Ladin E736997 entity
Predicate spouse P13 FINISHED
Object Katy Ladin
Katy Ladin is the wife of American actor Eric Ladin, known for his roles in television series such as "The Killing" and "Boardwalk Empire."
E1852424 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: Katy Ladin | Statement: [Eric Ladin, spouse, Katy Ladin]
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: Katy Ladin
Triple: [Eric Ladin, spouse, Katy Ladin]
Generated description
Katy Ladin is the wife of American actor Eric Ladin, known for his roles in television series such as "The Killing" and "Boardwalk Empire."

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_69f077ed54e08190bb02a744e8121a66 completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f661ef9e2481908788797adbd5c937 completed May 2, 2026, 8:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2550525c9481908ca50288d0dcfec3 completed June 7, 2026, 11:04 a.m.
NEDg Description generation batch_6a2554568f388190960bbfb09ed37b1d completed June 7, 2026, 11:21 a.m.
NED2 Entity disambiguation (via description) batch_6a2558e69dfc81908eea54a231ab38e7 completed June 7, 2026, 11:41 a.m.
Created at: April 28, 2026, 11:21 a.m.