Triple

T34565946
Position Surface form Disambiguated ID Type / Status
Subject Bill Williams E887481 entity
Predicate alsoKnownAs P39 FINISHED
Object Herman Katt
Herman Katt is the stage name of American actor Bill Williams, known for his work in mid-20th-century film and television.
E2119652 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: Herman Katt | Statement: [Bill Williams, alsoKnownAs, Herman Katt]
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: Herman Katt
Triple: [Bill Williams, alsoKnownAs, Herman Katt]
Generated description
Herman Katt is the stage name of American actor Bill Williams, known for his work in mid-20th-century film and television.

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_69f349d0c4d881908dd0950f5eb9ec0a completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f72065f4988190931aac5d785e7f64 completed May 3, 2026, 10:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37b25155b481908528f65804b5b123 completed June 21, 2026, 9:43 a.m.
NEDg Description generation batch_6a37b3212994819096c32d200bfcb4ef completed June 21, 2026, 9:47 a.m.
NED2 Entity disambiguation (via description) batch_6a37b396617c8190bc3fd123f565447a completed June 21, 2026, 9:49 a.m.
Created at: May 1, 2026, 2:02 a.m.