Triple

T35907151
Position Surface form Disambiguated ID Type / Status
Subject Michelangelo (Teenage Mutant Ninja Turtles) E1038502 entity
Predicate alias P39 FINISHED
Object Mike
Mike is the fun-loving, pizza-obsessed Teenage Mutant Ninja Turtle known for his nunchaku skills and laid-back, comedic personality.
E2160840 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: Mike | Statement: [Michelangelo (Teenage Mutant Ninja Turtles), alias, Mike]
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: Mike
Triple: [Michelangelo (Teenage Mutant Ninja Turtles), alias, Mike]
Generated description
Mike is the fun-loving, pizza-obsessed Teenage Mutant Ninja Turtle known for his nunchaku skills and laid-back, comedic personality.

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_69f76e2259608190bf6788a132e0d139 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7aa6fd79c8190b1a70068ace78068 completed May 3, 2026, 8:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38ae297d2c8190adbec34ef206cc9a completed June 22, 2026, 3:38 a.m.
NEDg Description generation batch_6a38ae942ddc8190b125685dbf7407e2 completed June 22, 2026, 3:40 a.m.
NED2 Entity disambiguation (via description) batch_6a38af0c461c8190a7332d1709b5553c completed June 22, 2026, 3:42 a.m.
Created at: May 3, 2026, 4:07 p.m.