Triple

T29778827
Position Surface form Disambiguated ID Type / Status
Subject Number 96 E755453 entity
Predicate productionCompany P490 FINISHED
Object Cash Harmon Television
Cash Harmon Television was an Australian television production company best known for creating the groundbreaking and controversial soap opera "Number 96" in the 1970s.
E1883558 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: Cash Harmon Television | Statement: [Number 96, productionCompany, Cash Harmon Television]
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: Cash Harmon Television
Triple: [Number 96, productionCompany, Cash Harmon Television]
Generated description
Cash Harmon Television was an Australian television production company best known for creating the groundbreaking and controversial soap opera "Number 96" in the 1970s.

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_69f0ef878574819088c867fd1a5c8b86 completed April 28, 2026, 5:33 p.m.
NER Named-entity recognition batch_69f674a46ba481908229b8389887074d completed May 2, 2026, 10:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26c8fdfe048190b0f35f80c49a1e05 completed June 8, 2026, 1:51 p.m.
NEDg Description generation batch_6a26cce42b208190b30d28fe1e55105b completed June 8, 2026, 2:08 p.m.
NED2 Entity disambiguation (via description) batch_6a26d421b5408190bfb77e624443fad8 completed June 8, 2026, 2:39 p.m.
Created at: April 28, 2026, 8:48 p.m.