Triple

T14013629
Position Surface form Disambiguated ID Type / Status
Subject The Shadow E337149 entity
Predicate producer P490 FINISHED
Object Harry A. Junkin
Harry A. Junkin was a radio and film producer best known for his work on the classic mystery series "The Shadow."
E1747871 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: Harry A. Junkin | Statement: [The Shadow, producer, Harry A. Junkin]
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: Harry A. Junkin
Triple: [The Shadow, producer, Harry A. Junkin]
Generated description
Harry A. Junkin was a radio and film producer best known for his work on the classic mystery series "The Shadow."

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_69d81c645c5c8190b1fd16a285a1b78a completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2f37d11481909159bdb9e1e8d38e completed April 14, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a121e64ef3081908b39a3c83e4440f3 completed May 23, 2026, 9:38 p.m.
NEDg Description generation batch_6a121fa58ae08190b70faa7e3c81eae8 completed May 23, 2026, 9:44 p.m.
NED2 Entity disambiguation (via description) batch_6a1220284ddc819085b3ca2cad3fbfa9 completed May 23, 2026, 9:46 p.m.
Created at: April 9, 2026, 10:19 p.m.