Triple

T30026659

Position	Surface form	Disambiguated ID	Type / Status
Subject	GeForce 500 Series	`E762897`	entity
Predicate	codenameExample	`P95299`	FINISHED
Object	GF110 GF110 is the graphics processing unit (GPU) architecture used in NVIDIA’s high-end GeForce 500 series cards, such as the GeForce GTX 580.	`E1897511`	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: GF110 | Statement: [GeForce 500 Series, codenameExample, GF110]

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: GF110
Triple: [GeForce 500 Series, codenameExample, GF110]

Generated description

GF110 is the graphics processing unit (GPU) architecture used in NVIDIA’s high-end GeForce 500 series cards, such as the GeForce GTX 580.

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

Target predicate: codenameExample
Context triple: [GeForce 500 Series, codenameExample, GF110]

A. codenameComponent
Indicates that one entity serves as the codename or code-designation assigned to another entity as its component or identifying label.
B. codenameContext chosen
Indicates that an entity is associated with or used as a codename within a particular contextual scope or situation.
C. codenameUser
Indicates that a user is assigned or associated with a particular codename.
D. codenameFormat
Indicates that an entity’s codename follows a specific prescribed format or pattern.
E. codenameNumber
Indicates that an entity is assigned or associated with a specific codename identifier represented as a number.
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_69f2246ee6e48190b69e837b913b398a`	completed	April 29, 2026, 3:31 p.m.
NER	Named-entity recognition	`batch_69f679ac62ac8190b1ab93bf5803e0a9`	completed	May 2, 2026, 10:24 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a273231a4d48190ada158d1f54bbaf1`	completed	June 8, 2026, 9:20 p.m.
NEDg	Description generation	`batch_6a27369f226081909c756c1db665159a`	completed	June 8, 2026, 9:39 p.m.
NED2	Entity disambiguation (via description)	`batch_6a2736f83b08819084c8fadd1fe1b6f2`	completed	June 8, 2026, 9:41 p.m.
PD	Predicate disambiguation	`batch_69f66ec9919881908a187bfc7c4df192`	completed	May 2, 2026, 9:38 p.m.

Created at: April 29, 2026, 6:48 p.m.