Triple

T29137430
Position Surface form Disambiguated ID Type / Status
Subject Wendy Corduroy E738542 entity
Predicate appearsInEpisode P795 FINISHED
Object "The Inconveniencing"
"The Inconveniencing" is an early episode of the animated series Gravity Falls in which Dipper tries to impress Wendy by joining her and her friends on a spooky adventure to an abandoned convenience store.
E1850563 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: "The Inconveniencing" | Statement: [Wendy Corduroy, appearsInEpisode, "The Inconveniencing"]
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: "The Inconveniencing"
Triple: [Wendy Corduroy, appearsInEpisode, "The Inconveniencing"]
Generated description
"The Inconveniencing" is an early episode of the animated series Gravity Falls in which Dipper tries to impress Wendy by joining her and her friends on a spooky adventure to an abandoned convenience store.

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_69f07cb3adb48190a9e0e169cd026634 completed April 28, 2026, 9:24 a.m.
NER Named-entity recognition batch_69f6626b8aa881908e1bf4776c2feea9 completed May 2, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2537da0ff08190aba9fbe8a80f020e completed June 7, 2026, 9:20 a.m.
NEDg Description generation batch_6a253c4ed4fc81908e479403c939f813 completed June 7, 2026, 9:39 a.m.
NED2 Entity disambiguation (via description) batch_6a25405315548190b3f08aace49bc72f completed June 7, 2026, 9:56 a.m.
Created at: April 28, 2026, 11:35 a.m.