Triple

T31041028

Position	Surface form	Disambiguated ID	Type / Status
Subject	IEC 60870‑5‑103	`E790994`	entity
Predicate	typicalPhysicalMedium	`P91476`	FINISHED
Object	RS‑485 RS‑485 is a balanced serial communication standard widely used in industrial and automation systems for robust, long-distance, multi-drop data transmission over twisted-pair cabling.	`E1943436`	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: RS‑485 | Statement: [IEC 60870‑5‑103, typicalPhysicalMedium, RS‑485]

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: RS‑485
Triple: [IEC 60870‑5‑103, typicalPhysicalMedium, RS‑485]

Generated description

RS‑485 is a balanced serial communication standard widely used in industrial and automation systems for robust, long-distance, multi-drop data transmission over twisted-pair cabling.

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

Target predicate: typicalPhysicalMedium
Context triple: [IEC 60870‑5‑103, typicalPhysicalMedium, RS‑485]

A. hasPhysicalMedium
Indicates that one entity serves as the tangible carrier or material form through which another entity exists, is stored, or is transmitted.
B. physicalMediumDependentSubtype
Indicates that one subtype or variation of something is specifically determined or constrained by the physical medium through which it exists or operates.
C. supportsPhysicalMedia
Indicates that one entity provides the capability to use, read, or handle physical media formats (such as discs, tapes, or printed materials) associated with another entity.
D. notableRecordingMedium
Indicates that an entity is notably recorded, documented, or expressed using a particular medium or format.
E. canonicalMedium chosen
Indicates the primary or standard medium through which something is most authoritatively or typically expressed, distributed, or experienced.
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_69f224ca2fa881908a3ac5fedf207b90`	completed	April 29, 2026, 3:33 p.m.
NER	Named-entity recognition	`batch_6a037c876524819098545e6037d3107d`	completed	May 12, 2026, 7:16 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a29185344e881909ed4a614c946f89b`	completed	June 10, 2026, 7:54 a.m.
NEDg	Description generation	`batch_6a291f14ef6081909fe22b4e0fd91876`	completed	June 10, 2026, 8:23 a.m.
NED2	Entity disambiguation (via description)	`batch_6a291f7964948190bb034c58df344a0b`	completed	June 10, 2026, 8:25 a.m.
PD	Predicate disambiguation	`batch_6a0379e5174c8190a0bdde7e381b7624`	completed	May 12, 2026, 7:05 p.m.

Created at: April 29, 2026, 8:59 p.m.