Triple

T38240747
Position Surface form Disambiguated ID Type / Status
Subject Master of Coin E1013752 entity
Predicate titleHolder P1911 FINISHED
Object Lord Rosby
Lord Rosby is a minor Westerosi noble from House Rosby in the A Song of Ice and Fire / Game of Thrones universe, known for his frailty, chronic cough, and service on the king’s small council.
E2260760 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: Lord Rosby | Statement: [Master of Coin, titleHolder, Lord Rosby]
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: Lord Rosby
Triple: [Master of Coin, titleHolder, Lord Rosby]
Generated description
Lord Rosby is a minor Westerosi noble from House Rosby in the A Song of Ice and Fire / Game of Thrones universe, known for his frailty, chronic cough, and service on the king’s small council.

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_69f76dd72a248190a5fe18db2bd1eb15 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fcb17ebfd081908b33491c49561f18 completed May 7, 2026, 3:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4185622a8081908ebf0d6544e75811 completed June 28, 2026, 8:34 p.m.
NEDg Description generation batch_6a4186e92d7c819089b247d880b67bd8 completed June 28, 2026, 8:41 p.m.
NED2 Entity disambiguation (via description) batch_6a41876913448190bc1221317c5a4cb2 completed June 28, 2026, 8:43 p.m.
Created at: May 3, 2026, 4:30 p.m.