Triple
T71519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Douglas fir |
E1430
|
entity |
| Predicate | needleLength |
P266
|
FINISHED |
| Object | about 2 to 3 centimeters |
—
|
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: about 2 to 3 centimeters | Statement: [Douglas fir, needleLength, about 2 to 3 centimeters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: needleLength Context triple: [Douglas fir, needleLength, about 2 to 3 centimeters]
-
A.
length
chosen
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
-
B.
width
Indicates the measurement of how wide an entity is, typically the extent of its horizontal dimension from side to side.
-
C.
arrowCount
Indicates the number of arrows associated with or involved in a given entity or interaction.
-
D.
meter
Indicates a measurement relationship where one entity quantifies the length, distance, or extent of another in meters.
-
E.
leafMargin
Indicates the type or pattern of the edge or border of a leaf (e.g., smooth, serrated, lobed).
- 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.