Triple

T32146271
Position Surface form Disambiguated ID Type / Status
Subject Stinky Pete the Prospector E821030 entity
Predicate associatedWithCharacter P1481 FINISHED
Object Jessie
Jessie is the spirited cowgirl doll from the Toy Story franchise, known for her adventurous personality and close friendship with Woody and Buzz Lightyear.
E237529 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: Jessie | Statement: [Stinky Pete the Prospector, associatedWithCharacter, Jessie]
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: Jessie
Triple: [Stinky Pete the Prospector, associatedWithCharacter, Jessie]
Generated description
Jessie is the spirited cowgirl doll from the Toy Story franchise, known for her adventurous personality and close friendship with Woody and Buzz Lightyear.

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_69f3490520d081909b2f1271dab75faa completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b9e219708190b17ca0d788527eeb completed May 3, 2026, 2:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f0130ec28819096a99c5149717ecb completed June 14, 2026, 7:29 p.m.
NEDg Description generation batch_6a2f01a456dc81908db13502eee7fde9 completed June 14, 2026, 7:31 p.m.
NED2 Entity disambiguation (via description) batch_6a2f02b7f21c81908bbf45cf1a616aab completed June 14, 2026, 7:36 p.m.
Created at: May 1, 2026, 12:31 a.m.