Triple

T25549389
Position Surface form Disambiguated ID Type / Status
Subject Rocketman (1997 film) E640395 entity
Predicate mainCharacter P1183 FINISHED
Object Fred Z. Randall
Fred Z. Randall is a bumbling yet brilliant computer programmer-turned-astronaut who serves as the comedic protagonist of the sci-fi comedy film "Rocketman" (1997).
E1761943 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: Fred Z. Randall | Statement: [Rocketman (1997 film), mainCharacter, Fred Z. Randall]
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: Fred Z. Randall
Triple: [Rocketman (1997 film), mainCharacter, Fred Z. Randall]
Generated description
Fred Z. Randall is a bumbling yet brilliant computer programmer-turned-astronaut who serves as the comedic protagonist of the sci-fi comedy film "Rocketman" (1997).

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_69e75dc101a881909fd33b02174e9768 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f8c4aec88190844c68cb10532363 completed May 2, 2026, 1:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1253528a8c8190b315f5a3baad027b completed May 24, 2026, 1:24 a.m.
NEDg Description generation batch_6a12545544f881909f0afd8459986559 completed May 24, 2026, 1:28 a.m.
NED2 Entity disambiguation (via description) batch_6a125879112c8190959380eaef8ccf19 completed May 24, 2026, 1:46 a.m.
Created at: April 21, 2026, 3:36 p.m.