Triple

T30441630

Position	Surface form	Disambiguated ID	Type / Status
Subject	大阪府豊中市	`E774459`	entity
Predicate	主な高等学校	`P159095`	FINISHED
Object	大阪府立桜塚高等学校大阪府立桜塚高等学校は、大阪府豊中市に位置する、進学実績と部活動の両面で知られる公立の伝統的な高等学校です。	`E1915361`	NE FINISHED

How this triple was built (3 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: 大阪府立桜塚高等学校 | Statement: [大阪府豊中市, 主な高等学校, 大阪府立桜塚高等学校]

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: 大阪府立桜塚高等学校
Triple: [大阪府豊中市, 主な高等学校, 大阪府立桜塚高等学校]

Generated description

大阪府立桜塚高等学校は、大阪府豊中市に位置する、進学実績と部活動の両面で知られる公立の伝統的な高等学校です。

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: 主な高等学校
Context triple: [大阪府豊中市, 主な高等学校, 大阪府立桜塚高等学校]

A. primaryHighSchool
Indicates that a person attended or is associated with a particular high school as their main or principal secondary education institution.
B. majorSchool
Indicates that one entity is the primary or most significant school or educational institution associated with another entity.
C. primaryUniversityType
Indicates the main or predominant classification of a university (e.g., by level, focus, or type) within a given context.
D. mainSchool chosen
Indicates that one school is the primary or most important school associated with a given entity.
E. 主な学部
Indicates a relationship where a university or institution is associated with its primary or main academic faculty/department.
F. None of above.

Provenance (6 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_69f22493ef9c8190ae8c2afcb7f994c8`	completed	April 29, 2026, 3:32 p.m.
NER	Named-entity recognition	`batch_69f6869948e481908901dbda23952cc0`	completed	May 2, 2026, 11:19 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a2798c1f3f08190aeb481c0c6a80485`	completed	June 9, 2026, 4:38 a.m.
NEDg	Description generation	`batch_6a279c3015cc8190aaeedc6222520b7b`	completed	June 9, 2026, 4:53 a.m.
NED2	Entity disambiguation (via description)	`batch_6a279ce453108190a68db27eb0b35665`	completed	June 9, 2026, 4:56 a.m.
PD	Predicate disambiguation	`batch_69f678d2196c8190b9d0d2fcd47cc539`	completed	May 2, 2026, 10:21 p.m.

Created at: April 29, 2026, 8:08 p.m.