Triple

T37918750
Position Surface form Disambiguated ID Type / Status
Subject Big Blue House E945896 entity
Predicate hasCharacter P2308 FINISHED
Object Shadow
Shadow is a playful, storytelling shadow character who appears on the wall to sing songs and share tales with Bear and his friends in the children's TV series "Bear in the Big Blue House."
E2248551 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: Shadow | Statement: [Big Blue House, hasCharacter, Shadow]
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: Shadow
Triple: [Big Blue House, hasCharacter, Shadow]
Generated description
Shadow is a playful, storytelling shadow character who appears on the wall to sing songs and share tales with Bear and his friends in the children's TV series "Bear in the Big Blue House."

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_69f76ef2ebd88190be5229f2621070b3 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbbd77c1388190aaa5c2f9b7c2a9d5 completed May 6, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4117ef25b081908bf4f98c83dafcd8 completed June 28, 2026, 12:47 p.m.
NEDg Description generation batch_6a412801c2f8819081519dfcd99e4d6a completed June 28, 2026, 1:56 p.m.
NED2 Entity disambiguation (via description) batch_6a41286de2948190a2a191e40db54545 completed June 28, 2026, 1:58 p.m.
Created at: May 3, 2026, 4:20 p.m.