Triple

T23498243
Position Surface form Disambiguated ID Type / Status
Subject House of Melo E571761 entity
Predicate hasNotableMember P304 FINISHED
Object João de Melo
João de Melo is a notable Portuguese nobleman and historical figure associated with the influential House of Melo.
E1599504 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: João de Melo | Statement: [House of Melo, hasNotableMember, João de Melo]
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: João de Melo
Triple: [House of Melo, hasNotableMember, João de Melo]
Generated description
João de Melo is a notable Portuguese nobleman and historical figure associated with the influential House of Melo.

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_69e245b4829881909b77a70e942bbd54 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a7e184ec8190aff3677c9b00a8f2 completed April 29, 2026, 6:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f537cc0f48190977194743518a8f1 completed May 21, 2026, 6:48 p.m.
NEDg Description generation batch_6a0f57738df881908df1142df2cb2ff3 completed May 21, 2026, 7:05 p.m.
NED2 Entity disambiguation (via description) batch_6a0f57e13770819083c5d08330e0cd02 completed May 21, 2026, 7:07 p.m.
Created at: April 17, 2026, 6:06 p.m.