Triple

T30115514
Position Surface form Disambiguated ID Type / Status
Subject Hauteville House E765404 entity
Predicate hasPart P35 FINISHED
Object red room
The red room is a richly decorated chamber in Hauteville House, Victor Hugo’s former residence on Guernsey, known for its vivid color scheme and distinctive interior design.
 E1898861 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: red room | Statement: [Hauteville House, hasPart, red room]
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: red room
Triple: [Hauteville House, hasPart, red room]
Generated description
The red room is a richly decorated chamber in Hauteville House, Victor Hugo’s former residence on Guernsey, known for its vivid color scheme and distinctive interior design.

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_69f22475ad7c8190be7f9541044a0bbb completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67dc398ac819098691c977e16094d completed May 2, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2743393f9c819089ac53a51e56df18 completed June 8, 2026, 10:33 p.m.
NEDg Description generation batch_6a274402537c8190ade00dfc5d92e722 completed June 8, 2026, 10:36 p.m.
NED2 Entity disambiguation (via description) batch_6a2744f156208190b3617a3623b8b3ec completed June 8, 2026, 10:40 p.m.
Created at: April 29, 2026, 7:11 p.m.