Triple

T13469381
Position Surface form Disambiguated ID Type / Status
Subject Chuck Palahniuk E311587 entity
Predicate employer P7 FINISHED
Object Freightliner E412319 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: Freightliner | Statement: [Chuck Palahniuk, employer, Freightliner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Freightliner
Context triple: [Chuck Palahniuk, employer, Freightliner]
  • A. Freightliner chosen
    Freightliner is a major American manufacturer of heavy-duty and commercial trucks, best known for its long-haul semi-trucks and part of the Daimler AG family of brands.
  • B. Peterbilt
    Peterbilt is an American manufacturer of premium heavy-duty and medium-duty trucks known for their durability, performance, and iconic styling.
  • C. Mack Trucks
    Mack Trucks is a historic American truck manufacturing company best known for its heavy-duty commercial vehicles and iconic bulldog logo.
  • D. Kenworth
    Kenworth is a prominent American manufacturer of heavy-duty and medium-duty trucks known for their durability and use in commercial freight and vocational applications.
  • E. International Trucks
    International Trucks is a major American manufacturer of commercial trucks and diesel engines, known for producing a wide range of medium- and heavy-duty vehicles for freight, construction, and vocational use.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d806a938b8819097ec43a2229fc7f9 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf21e46081908a00c9acf54f270f completed April 12, 2026, 2:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7462bcb848190804a48f1a50a0c71 completed May 3, 2026, 12:57 p.m.
Created at: April 9, 2026, 9:42 p.m.