Triple
T9305533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colorado blue spruce |
E223874
|
entity |
| Predicate | needleCrossSection |
P73088
|
FINISHED |
| Object | four-angled |
—
|
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: four-angled | Statement: [Colorado blue spruce, needleCrossSection, four-angled]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: needleCrossSection Context triple: [Colorado blue spruce, needleCrossSection, four-angled]
-
A.
crossesSectionOf
Indicates that one entity passes through or over a specific segment or portion of another entity.
-
B.
hasCrossSection
chosen
Indicates that one entity represents or possesses the cross-sectional shape, profile, or slice of another entity.
-
C.
needlesPerFascicle
Indicates the number of individual needles contained within a single fascicle (bundle) of needles.
-
D.
needleArrangement
Indicates how needles are positioned or organized relative to each other in a given context.
-
E.
featuresCrossShape
Indicates that something has a form, pattern, or configuration resembling a cross shape.
- 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_69ca8424d0f08190831e2e93c6533aeb |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd1da7c1e08190af19169f5d806cde |
completed | April 1, 2026, 1:29 p.m. |
| PD | Predicate disambiguation | batch_69cc7a5ef1908190bc5ca166bb895af6 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:36 p.m.