Triple

T32035795
Position Surface form Disambiguated ID Type / Status
Subject Star Command E818090 entity
Predicate hasMember P10 FINISHED
Object Booster Munchapper
Booster Munchapper is a large, good-natured alien and rookie Space Ranger from the "Buzz Lightyear of Star Command" animated series, known for his strength, enthusiasm, and loyalty to his team.
E1988777 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: Booster Munchapper | Statement: [Star Command, hasMember, Booster Munchapper]
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: Booster Munchapper
Triple: [Star Command, hasMember, Booster Munchapper]
Generated description
Booster Munchapper is a large, good-natured alien and rookie Space Ranger from the "Buzz Lightyear of Star Command" animated series, known for his strength, enthusiasm, and loyalty to his team.

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_69f348fbc8148190b3c0f95d4772b153 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b49b23448190a6c600187b66c7c7 completed May 3, 2026, 2:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2ed4f6101881909ca70d0faf9a2a16 completed June 14, 2026, 4:21 p.m.
NEDg Description generation batch_6a2ed5c07e34819098385a0d7a928fa4 completed June 14, 2026, 4:24 p.m.
NED2 Entity disambiguation (via description) batch_6a2ed7379d088190b7481d5c7eb61b9f completed June 14, 2026, 4:30 p.m.
Created at: May 1, 2026, 12:18 a.m.