Triple

T25211313
Position Surface form Disambiguated ID Type / Status
Subject 704 Hauser E631693 entity
Predicate hasCharacter P2308 FINISHED
Object Goodie Cumberbatch
Goodie Cumberbatch is a fictional character from the short-lived 1994 American sitcom "704 Hauser," which revisited the iconic setting of "All in the Family" with a new family and contemporary social issues.
E1668039 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: Goodie Cumberbatch | Statement: [704 Hauser, hasCharacter, Goodie Cumberbatch]
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: Goodie Cumberbatch
Triple: [704 Hauser, hasCharacter, Goodie Cumberbatch]
Generated description
Goodie Cumberbatch is a fictional character from the short-lived 1994 American sitcom "704 Hauser," which revisited the iconic setting of "All in the Family" with a new family and contemporary social issues.

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_69e75a8d1aa48190a4320acd3654762c completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f47b8918fc819080825ed92fb3a1a7 completed May 1, 2026, 10:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105d32eee88190ba3f287e86b79f5c completed May 22, 2026, 1:42 p.m.
NEDg Description generation batch_6a105e54aa3081909184efa8240194eb completed May 22, 2026, 1:47 p.m.
NED2 Entity disambiguation (via description) batch_6a105f91c8808190b902d606e0ad6d0e completed May 22, 2026, 1:52 p.m.
Created at: April 21, 2026, 12:58 p.m.