Triple
T71476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Douglas fir |
E1430
|
entity |
| Predicate | woodColor |
P60
|
FINISHED |
| Object | light brown to reddish brown |
—
|
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: light brown to reddish brown | Statement: [Douglas fir, woodColor, light brown to reddish brown]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: woodColor Context triple: [Douglas fir, woodColor, light brown to reddish brown]
-
A.
woodProperty
Indicates that one entity specifies or characterizes a property or attribute of wood associated with another entity.
-
B.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
C.
colors
chosen
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
D.
oakAffinity
Indicates a special connection, preference, or strong association between an entity and oak (such as oak trees, wood, or oak-related environments).
-
E.
material
Indicates that one entity is physically composed of, made from, or constructed using the substance or material represented by the other 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24f6997c081908b202f937eb2b14f |
completed | Feb. 28, 2026, 2:14 a.m. |
| PD | Predicate disambiguation | batch_69a24eab7f408190a8275cb82474f575 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.