Triple
T37457709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shadowreaper Anduin |
E930839
|
entity |
| Predicate | mechanicCategory |
P48192
|
FINISHED |
| Object | Board clear |
—
|
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: Board clear | Statement: [Shadowreaper Anduin, mechanicCategory, Board clear]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mechanicCategory Context triple: [Shadowreaper Anduin, mechanicCategory, Board clear]
-
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.
powertrainCategory
Indicates the classification of a vehicle’s powertrain based on how it delivers propulsion (e.g., internal combustion, hybrid, electric).
-
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.
featuresMechanic
chosen
Indicates that something includes or incorporates a particular mechanic as part of its design or functionality.
-
E.
drivetrainCategory
Indicates the type or classification of a vehicle’s drivetrain system (e.g., FWD, RWD, AWD) associated with an entity.
- F. None of above.
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_69f76ec1a1148190b0a961f188d621b0 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba68077788190b311e027435fcf87 |
completed | May 6, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fba34c65ac8190b298f0f00d1dcc0e |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.