Triple

T34669478

Position	Surface form	Disambiguated ID	Type / Status
Subject	Kenneth Young	`E890337`	entity
Predicate	participatedIn	`P149`	FINISHED
Object	Develop:Brighton conference talks Develop:Brighton conference talks are sessions at a UK-based game development industry event where professionals share insights, techniques, and experiences across all aspects of making games.	`E2105896`	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: Develop:Brighton conference talks | Statement: [Kenneth Young, participatedIn, Develop:Brighton conference talks]

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: Develop:Brighton conference talks
Triple: [Kenneth Young, participatedIn, Develop:Brighton conference talks]

Generated description

Develop:Brighton conference talks are sessions at a UK-based game development industry event where professionals share insights, techniques, and experiences across all aspects of making games.

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_69f349d9c59481908b36baa0be093aea`	completed	April 30, 2026, 12:23 p.m.
NER	Named-entity recognition	`batch_69f722fa31248190a1c9081ce8cfa37b`	completed	May 3, 2026, 10:27 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a3749079fdc81908004d7a554eebd5f`	completed	June 21, 2026, 2:14 a.m.
NEDg	Description generation	`batch_6a374a4c38c88190bdd7ad54e6a7a714`	completed	June 21, 2026, 2:19 a.m.
NED2	Entity disambiguation (via description)	`batch_6a374ab6a5388190ad9d0601f27c6748`	completed	June 21, 2026, 2:21 a.m.

Created at: May 1, 2026, 2:05 a.m.