Triple

T25100054

Position	Surface form	Disambiguated ID	Type / Status
Subject	KAI Commuter	`E628696`	entity
Predicate	operatesOn	`P23`	FINISHED
Object	Jakarta–Bekasi line The Jakarta–Bekasi line is a commuter rail corridor in the Greater Jakarta area of Indonesia that connects central Jakarta with the eastern city of Bekasi as part of the KRL Commuterline network.	`E1666459`	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: Jakarta–Bekasi line | Statement: [KAI Commuter, operatesOn, Jakarta–Bekasi line]

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: Jakarta–Bekasi line
Triple: [KAI Commuter, operatesOn, Jakarta–Bekasi line]

Generated description

The Jakarta–Bekasi line is a commuter rail corridor in the Greater Jakarta area of Indonesia that connects central Jakarta with the eastern city of Bekasi as part of the KRL Commuterline network.

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_69e2ff3071548190b62d1ac237397197`	completed	April 18, 2026, 3:49 a.m.
NER	Named-entity recognition	`batch_69f464bc496081909bad8c973386eea4`	completed	May 1, 2026, 8:30 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a105cf104ac8190bc3c3be3076a5a7c`	completed	May 22, 2026, 1:41 p.m.
NEDg	Description generation	`batch_6a105dd12cd08190b382c57952107fa6`	completed	May 22, 2026, 1:44 p.m.
NED2	Entity disambiguation (via description)	`batch_6a105edf54888190a3b77f63eb867749`	completed	May 22, 2026, 1:49 p.m.

Created at: April 18, 2026, 6:25 a.m.