Triple

T37771558

Position	Surface form	Disambiguated ID	Type / Status
Subject	Kasuga Station	`E941559`	entity
Predicate	hasStationCodeOnToeiMitaLine	`P95306`	FINISHED
Object	I-12 I-12 is the station code assigned to Kasuga Station on Tokyo’s Toei Mita Line.	`E2242403`	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: I-12 | Statement: [Kasuga Station, hasStationCodeOnToeiMitaLine, I-12]

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: I-12
Triple: [Kasuga Station, hasStationCodeOnToeiMitaLine, I-12]

Generated description

I-12 is the station code assigned to Kasuga Station on Tokyo’s Toei Mita Line.

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

Target predicate: hasStationCodeOnToeiMitaLine
Context triple: [Kasuga Station, hasStationCodeOnToeiMitaLine, I-12]

A. ToeiSubwayStationNumber chosen
Indicates the identification number assigned to a station within the Toei Subway system.
B. TokyuStationNumber
Indicates that an entity is assigned a specific station number within the Tokyu railway network.
C. adjacentStationOnToeiMitaLine
Indicates that one station is directly next to another station along the Toei Mita railway line, with no other stations in between.
D. hasAdjacentStationOnYurakuchoLine
Indicates that one station is directly next to another station along the Yurakucho Line.
E. TokyoMetroStationNumber
Indicates that an entity is assigned a specific official station number within the Tokyo Metro railway network.
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_69f76ee4431881908f87e8892a9f39f3`	completed	May 3, 2026, 3:51 p.m.
NER	Named-entity recognition	`batch_6a008ebb22408190a2293bced40a7e53`	completed	May 10, 2026, 1:57 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a40e08b47b481909a7399fdc066157e`	completed	June 28, 2026, 8:51 a.m.
NEDg	Description generation	`batch_6a40e20333b48190be82559cd58a2a12`	completed	June 28, 2026, 8:57 a.m.
NED2	Entity disambiguation (via description)	`batch_6a40e65094e481909fc7d4cafd4fdba7`	completed	June 28, 2026, 9:16 a.m.
PD	Predicate disambiguation	`batch_6a008e8715dc8190ab23292605901bf4`	completed	May 10, 2026, 1:56 p.m.

Created at: May 3, 2026, 4:19 p.m.