Triple

T37458864
Position Surface form Disambiguated ID Type / Status
Subject Tinkertown Technician E930866 entity
Predicate mechanicTheme P188947 FINISHED
Object Spare Parts LITERAL 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: Spare Parts | Statement: [Tinkertown Technician, mechanicTheme, Spare Parts]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: mechanicTheme
Context triple: [Tinkertown Technician, mechanicTheme, Spare Parts]
  • A. mechanicalExpertise
    Indicates that one entity possesses specialized knowledge or skill in understanding, operating, or repairing mechanical systems or devices in relation to another entity or context.
  • B. featuresMechanic
    Indicates that something includes or incorporates a particular mechanic as part of its design or functionality.
  • C. mechanics
    Indicates that an entity is involved in the study, design, or application of forces and motion (i.e., mechanical principles) in relation to another entity or system.
  • D. keyMechanic
    Indicates that the referenced element functions as a central or essential gameplay mechanic within a system or experience.
  • E. ammoMechanic
    Indicates a relationship where one entity functions as the mechanic or system responsible for handling, managing, or affecting another entity’s ammunition.
  • F. None of above. chosen

Provenance (4 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_69f76ec1a1148190b0a961f188d621b0 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fbaf18085481908c774e8f8bbb9a41 completed May 6, 2026, 9:14 p.m.
PD Predicate disambiguation batch_69fbadf1e6008190a71bbd196ba06844 completed May 6, 2026, 9:09 p.m.
PDg Predicate description generation batch_69fbaebbb7f88190b4edfd9b83550aad completed May 6, 2026, 9:12 p.m.
Created at: May 3, 2026, 4:17 p.m.