Triple

T29347248
Position Surface form Disambiguated ID Type / Status
Subject Illustrations for "Through the Looking-Glass, and What Alice Found There" E744203 entity
Predicate depicts P1581 FINISHED
Object Alice
Alice is the curious young heroine of Lewis Carroll’s classic fantasy novels, whose adventures in surreal, dreamlike worlds have made her an enduring icon of children’s literature.
E1589520 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: Alice | Statement: [Illustrations for "Through the Looking-Glass, and What Alice Found There", depicts, Alice]
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: Alice
Triple: [Illustrations for "Through the Looking-Glass, and What Alice Found There", depicts, Alice]
Generated description
Alice is the curious young heroine of Lewis Carroll’s classic fantasy novels, whose adventures in surreal, dreamlike worlds have made her an enduring icon of children’s literature.

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_69f0a79a2d748190bc30abd469298b37 completed April 28, 2026, 12:27 p.m.
NER Named-entity recognition batch_69f6695868ec8190acc362e10b252ace completed May 2, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25a85052b48190abcc50705f80f9ca completed June 7, 2026, 5:20 p.m.
NEDg Description generation batch_6a25ad48a5e881908ec91dcd6da78001 completed June 7, 2026, 5:41 p.m.
NED2 Entity disambiguation (via description) batch_6a25ada3d5888190b35903316b8b3e03 completed June 7, 2026, 5:43 p.m.
Created at: April 28, 2026, 2:03 p.m.