Triple
T37664959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crying Obsidian |
E937799
|
entity |
| Predicate | toolEfficiency |
P188516
|
FINISHED |
| Object | pickaxe is fastest |
—
|
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: pickaxe is fastest | Statement: [Crying Obsidian, toolEfficiency, pickaxe is fastest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: toolEfficiency Context triple: [Crying Obsidian, toolEfficiency, pickaxe is fastest]
-
A.
efficiency
Indicates how effectively an entity converts inputs (such as time, energy, or resources) into desired outputs or results.
-
B.
efficiencyComparedToManual
Indicates how the efficiency of a process or system compares to performing the same task manually.
-
C.
maximumEfficiency
Indicates that an entity operates at its highest possible level of performance or productivity under given conditions.
-
D.
toolIn
Indicates that one entity is a tool or instrument used in or associated with another entity or context.
-
E.
sampleEfficiency
Indicates how effectively a method or system learns or performs using a limited number of samples or data points.
- 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_69f76ed6df7c8190b018e5baea716ceb |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaa19e4a88190b04f26c0d4e708fd |
completed | May 6, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69fba887821c8190ae93ef1dd389e9c8 |
completed | May 6, 2026, 8:45 p.m. |
| PDg | Predicate description generation | batch_69fba9ddef488190b785d332580650f0 |
completed | May 6, 2026, 8:51 p.m. |
Created at: May 3, 2026, 4:18 p.m.