Triple

T37228481
Position Surface form Disambiguated ID Type / Status
Subject The Perils of Penelope Pitstop E923067 entity
Predicate character P662 FINISHED
Object Zippy
Zippy is a supporting character from the animated television series "The Perils of Penelope Pitstop," known for appearing alongside the show's slapstick, adventure-driven storylines.
E2219812 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: Zippy | Statement: [The Perils of Penelope Pitstop, character, Zippy]
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: Zippy
Triple: [The Perils of Penelope Pitstop, character, Zippy]
Generated description
Zippy is a supporting character from the animated television series "The Perils of Penelope Pitstop," known for appearing alongside the show's slapstick, adventure-driven storylines.

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_69f76ea7f0008190b31b8e30f3d05a71 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb36a39dbc81909dadcf056f52aaaf completed May 6, 2026, 12:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40637db908819099c0bdbde51e760f completed June 27, 2026, 11:57 p.m.
NEDg Description generation batch_6a4065312e888190a413095b2612a863 completed June 28, 2026, 12:05 a.m.
NED2 Entity disambiguation (via description) batch_6a40659ef09c8190bd9fb4538bdfb3b1 completed June 28, 2026, 12:06 a.m.
Created at: May 3, 2026, 4:15 p.m.