Triple

T35071891
Position Surface form Disambiguated ID Type / Status
Subject His Toy, His Dream, His Rest E1011900 entity
Predicate mainCharacter P1183 FINISHED
Object Henry
Henry is the central protagonist of the children's story "His Toy, His Dream, His Rest," around whom the narrative's emotional and imaginative journey revolves.
E2127872 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: Henry | Statement: [His Toy, His Dream, His Rest, mainCharacter, Henry]
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: Henry
Triple: [His Toy, His Dream, His Rest, mainCharacter, Henry]
Generated description
Henry is the central protagonist of the children's story "His Toy, His Dream, His Rest," around whom the narrative's emotional and imaginative journey revolves.

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_69f76dd193108190af2528186f25b72a completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7865578d48190bf90e470634fd97d completed May 3, 2026, 5:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37d94415448190908b5aaa7a70c44d completed June 21, 2026, 12:29 p.m.
NEDg Description generation batch_6a37da40e40c8190a4d5cb39b085cb7f completed June 21, 2026, 12:34 p.m.
NED2 Entity disambiguation (via description) batch_6a37db6e50948190a9437eab692a4ac7 completed June 21, 2026, 12:39 p.m.
Created at: May 3, 2026, 4:01 p.m.