Triple
T14652775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huon pine |
E344029
|
entity |
| Predicate | timberWorkability |
P1357
|
FINISHED |
| Object | easily worked |
—
|
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: easily worked | Statement: [Huon pine, timberWorkability, easily worked]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timberWorkability Context triple: [Huon pine, timberWorkability, easily worked]
-
A.
woodProperty
chosen
Indicates that one entity specifies or characterizes a property or attribute of wood associated with another entity.
-
B.
topWood
Indicates that one entity is made of or features a particular type of wood used specifically for its top surface or top section.
-
C.
isWoodenStructure
Indicates that the subject is a structure primarily made of wood or constructed using wooden components.
-
D.
includesTimberGenus
Indicates that one entity contains or encompasses a timber-related genus as part of its composition or classification.
-
E.
treeUse
Indicates the way in which a tree is utilized or purposed within a given context.
- 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_69d822e1a2cc81908e5bb93cf61ce3cc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb517e7648190b9fc73d6cdbb68de |
completed | April 14, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69de6576f0208190aa94d995e797ac38 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:27 a.m.