Triple

T27693628
Position Surface form Disambiguated ID Type / Status
Subject Judy Tobin E698223 entity
Predicate hasGrandfather P979 FINISHED
Object Tuntley Tobin
Tuntley Tobin is a member of the Tobin family and the grandfather of Judy Tobin in the animated series "The Great North."
E1785281 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: Tuntley Tobin | Statement: [Judy Tobin, hasGrandfather, Tuntley Tobin]
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: Tuntley Tobin
Triple: [Judy Tobin, hasGrandfather, Tuntley Tobin]
Generated description
Tuntley Tobin is a member of the Tobin family and the grandfather of Judy Tobin in the animated series "The Great North."

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_69ef590ea74081908f0cd7500d85fa27 completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f635798ac88190a8064ecac0f27e07 completed May 2, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12e452b29c8190bc6e0f03803e8ac7 completed May 24, 2026, 11:43 a.m.
NEDg Description generation batch_6a12e53aea408190b4a87d3851aa1340 completed May 24, 2026, 11:47 a.m.
NED2 Entity disambiguation (via description) batch_6a12e5acc5c8819081be9900ea407d65 completed May 24, 2026, 11:49 a.m.
Created at: April 27, 2026, 2:53 p.m.