Triple

T29938132

Position	Surface form	Disambiguated ID	Type / Status
Subject	GeForce 7 Series	`E760423`	entity
Predicate	includesModel	`P1393`	FINISHED
Object	GeForce 7600 GS The GeForce 7600 GS is a mid-range NVIDIA graphics card from the GeForce 7 series, known for offering solid performance and features for mainstream gaming and multimedia use at the time of its release.	`E1907075`	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: GeForce 7600 GS | Statement: [GeForce 7 Series, includesModel, GeForce 7600 GS]

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: GeForce 7600 GS
Triple: [GeForce 7 Series, includesModel, GeForce 7600 GS]

Generated description

The GeForce 7600 GS is a mid-range NVIDIA graphics card from the GeForce 7 series, known for offering solid performance and features for mainstream gaming and multimedia use at the time of its release.

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_69f22463f3648190a603c3ff305c660b`	completed	April 29, 2026, 3:31 p.m.
NER	Named-entity recognition	`batch_69f677d7ab2c8190a26f161c559ed05b`	completed	May 2, 2026, 10:16 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a276ed75e78819091e642ebfb3002f3`	completed	June 9, 2026, 1:39 a.m.
NEDg	Description generation	`batch_6a276f94e1a48190ad495f35d898d234`	completed	June 9, 2026, 1:42 a.m.
NED2	Entity disambiguation (via description)	`batch_6a2770212730819089e1e0487460f634`	completed	June 9, 2026, 1:45 a.m.

Created at: April 29, 2026, 6:21 p.m.