Triple

T35124214

Position	Surface form	Disambiguated ID	Type / Status
Subject	Fizir F19	`E1014250`	entity
Predicate	hasManufacturer	`P4022`	FINISHED
Object	Yugoslav aircraft industry The Yugoslav aircraft industry was the national aviation sector of the former Yugoslavia, responsible for designing and producing a range of military and civilian aircraft in the 20th century.	`E278143`	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: Yugoslav aircraft industry | Statement: [Fizir F19, hasManufacturer, Yugoslav aircraft industry]

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: Yugoslav aircraft industry
Triple: [Fizir F19, hasManufacturer, Yugoslav aircraft industry]

Generated description

The Yugoslav aircraft industry was the national aviation sector of the former Yugoslavia, responsible for designing and producing a range of military and civilian aircraft in the 20th century.

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_69f76dd8b6948190aaa32b081816bd94`	completed	May 3, 2026, 3:46 p.m.
NER	Named-entity recognition	`batch_69f78c44083881909b1cd377ab1cd592`	completed	May 3, 2026, 5:56 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a37d0093bd88190ae09e7de1a3c3c9c`	completed	June 21, 2026, 11:50 a.m.
NEDg	Description generation	`batch_6a37d11be0348190b8016348f557c38a`	completed	June 21, 2026, 11:55 a.m.
NED2	Entity disambiguation (via description)	`batch_6a37d281c69c8190a52f4d7fe37e0891`	completed	June 21, 2026, 12:01 p.m.

Created at: May 3, 2026, 4:01 p.m.