Triple

T26548937
Position Surface form Disambiguated ID Type / Status
Subject Shō Hashi E671621 entity
Predicate associatedWith P37 FINISHED
Object Sashiki Castle
Sashiki Castle is a former Ryukyuan gusuku (fortress) in Okinawa, Japan, historically linked to the rise of King Shō Hashi and the unification of the Ryukyu Kingdom.
E1914588 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: Sashiki Castle | Statement: [Shō Hashi, associatedWith, Sashiki Castle]
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: Sashiki Castle
Triple: [Shō Hashi, associatedWith, Sashiki Castle]
Generated description
Sashiki Castle is a former Ryukyuan gusuku (fortress) in Okinawa, Japan, historically linked to the rise of King Shō Hashi and the unification of the Ryukyu Kingdom.

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_69eeb32163f08190af5f81282738e27a completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f614380cac819085b58a4e1be207db completed May 2, 2026, 3:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a279889658881909925cabc3245dccc completed June 9, 2026, 4:37 a.m.
NEDg Description generation batch_6a2799a448a08190846b636fe84f73ce completed June 9, 2026, 4:42 a.m.
NED2 Entity disambiguation (via description) batch_6a279a2c8d0c8190aa6d61585c23d0ab completed June 9, 2026, 4:44 a.m.
Created at: April 27, 2026, 1:46 a.m.