Triple

T27673333
Position Surface form Disambiguated ID Type / Status
Subject Kameari area E697716 entity
Predicate hasLandmark P105 FINISHED
Object Kameari Station south exit plaza
Kameari Station south exit plaza is a well-known public square in Tokyo’s Kameari district, often recognized as a local gathering spot and gateway to the surrounding shopping streets and neighborhood attractions.
E1782858 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: Kameari Station south exit plaza | Statement: [Kameari area, hasLandmark, Kameari Station south exit plaza]
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: Kameari Station south exit plaza
Triple: [Kameari area, hasLandmark, Kameari Station south exit plaza]
Generated description
Kameari Station south exit plaza is a well-known public square in Tokyo’s Kameari district, often recognized as a local gathering spot and gateway to the surrounding shopping streets and neighborhood attractions.

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_69ef590d458c81909583290c3cd0478b completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f63531e6c88190b586d5139a20e6e7 completed May 2, 2026, 5:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12e44f26f88190bd70fa3f8c423226 completed May 24, 2026, 11:43 a.m.
NEDg Description generation batch_6a12e528463c819087d479b960e660d2 completed May 24, 2026, 11:46 a.m.
NED2 Entity disambiguation (via description) batch_6a12e58a24a08190baec56a49e9f24e8 completed May 24, 2026, 11:48 a.m.
Created at: April 27, 2026, 2:42 p.m.