Triple

T36729117

Position	Surface form	Disambiguated ID	Type / Status
Subject	Nike Air Max	`E907279`	entity
Predicate	notableModel	`P1503`	FINISHED
Object	Nike Air Max 95 The Nike Air Max 95 is a landmark running shoe known for its layered, gradient upper, visible forefoot and heel Air cushioning, and influential role in 1990s sneaker culture.	`E2197512`	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: Nike Air Max 95 | Statement: [Nike Air Max, notableModel, Nike Air Max 95]

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: Nike Air Max 95
Triple: [Nike Air Max, notableModel, Nike Air Max 95]

Generated description

The Nike Air Max 95 is a landmark running shoe known for its layered, gradient upper, visible forefoot and heel Air cushioning, and influential role in 1990s sneaker culture.

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_69f76e746e4c8190a0d05cc6d57a643e`	completed	May 3, 2026, 3:49 p.m.
NER	Named-entity recognition	`batch_69f7c8a250f08190a8842bc73cff8962`	completed	May 3, 2026, 10:13 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a3c172983088190ad075cf8cdfddc7a`	completed	June 24, 2026, 5:43 p.m.
NEDg	Description generation	`batch_6a3c17eb1a9c81909dff2e396edbe247`	completed	June 24, 2026, 5:46 p.m.
NED2	Entity disambiguation (via description)	`batch_6a3c6c95ba308190825d5700d4b6d605`	completed	June 24, 2026, 11:47 p.m.

Created at: May 3, 2026, 4:12 p.m.