Triple

T27098319
Position Surface form Disambiguated ID Type / Status
Subject Maeda Toshinaga E686369 entity
Predicate mother P120 FINISHED
Object Maeda Matsu
Maeda Matsu was a prominent noblewoman of Japan’s Sengoku and early Edo periods, renowned for her political acumen, loyalty to the Maeda clan, and role in navigating the family through turbulent feudal conflicts.
E1759617 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: Maeda Matsu | Statement: [Maeda Toshinaga, mother, Maeda Matsu]
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: Maeda Matsu
Triple: [Maeda Toshinaga, mother, Maeda Matsu]
Generated description
Maeda Matsu was a prominent noblewoman of Japan’s Sengoku and early Edo periods, renowned for her political acumen, loyalty to the Maeda clan, and role in navigating the family through turbulent feudal conflicts.

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_69ef1489f8b481908e24a1985982bd26 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f623b2b1048190a718869c992aa3c5 completed May 2, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12537344c8819089d18c09a6d7028a completed May 24, 2026, 1:25 a.m.
NEDg Description generation batch_6a12540036908190876fb0c9e9737862 completed May 24, 2026, 1:27 a.m.
NED2 Entity disambiguation (via description) batch_6a1254f46d288190aa6f45f8c8e9007d completed May 24, 2026, 1:31 a.m.
Created at: April 27, 2026, 8:46 a.m.