Triple

T34130383

Position	Surface form	Disambiguated ID	Type / Status
Subject	Dhanbad railway division	`E875406`	entity
Predicate	hasRailwayDivisionCode	`P30519`	FINISHED
Object	DHN DHN is the railway division code for the Dhanbad railway division of Indian Railways.	`E2082102`	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: DHN | Statement: [Dhanbad railway division, hasRailwayDivisionCode, DHN]

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: DHN
Triple: [Dhanbad railway division, hasRailwayDivisionCode, DHN]

Generated description

DHN is the railway division code for the Dhanbad railway division of Indian Railways.

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

Target predicate: hasRailwayDivisionCode
Context triple: [Dhanbad railway division, hasRailwayDivisionCode, DHN]

A. railwayDivision
Indicates that one administrative railway division is responsible for, manages, or encompasses another railway unit, line, or area within a rail network.
B. railwayDivisionHeadquartersOf
Indicates that one location serves as the administrative headquarters for a specified railway division.
C. hasDivisionCode chosen
Indicates that an entity is associated with a specific division identifier or code within an organizational or classification structure.
D. railwayAdministrationCode
Indicates the code assigned by a railway authority or administration that identifies which railway organization is responsible for or manages a given entity.
E. hasRailwayZone
Indicates that a location or railway entity falls under the jurisdiction or coverage area of a specific railway zone.
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_69f349aa33848190a2e6c5e4533c8444`	completed	April 30, 2026, 12:23 p.m.
NER	Named-entity recognition	`batch_69fd05ba6b2c81909c62b46237d10365`	completed	May 7, 2026, 9:35 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a36b7794f8481908da523cce7f3de9a`	completed	June 20, 2026, 3:53 p.m.
NEDg	Description generation	`batch_6a36b87e7e588190abb7ce4c5ea03b0f`	completed	June 20, 2026, 3:57 p.m.
NED2	Entity disambiguation (via description)	`batch_6a36b9b97df48190bde30fd9c4e0d823`	completed	June 20, 2026, 4:03 p.m.
PD	Predicate disambiguation	`batch_69fd03039e48819082b6e12c5453885a`	completed	May 7, 2026, 9:24 p.m.

Created at: May 1, 2026, 1:53 a.m.