Triple
T7934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American elm |
E156
|
entity |
| Predicate | leafShape |
P577
|
FINISHED |
| Object | ovate |
—
|
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: ovate | Statement: [American elm, leafShape, ovate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leafShape Context triple: [American elm, leafShape, ovate]
-
A.
mouth
Indicates that one entity is the mouth (oral opening) of another entity, typically serving as the location for ingestion, speech, or related functions.
-
B.
length
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
-
C.
hasDiminutive
Indicates that one entity is a diminutive form or smaller/affectionate variant of another entity.
-
D.
area
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
-
E.
wears
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
- 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_69a23bb612708190b09f25385e4b63d1 |
completed | Feb. 28, 2026, 12:49 a.m. |
| NER | Named-entity recognition | batch_69a2407916ac8190b76d2e6690efaef3 |
completed | Feb. 28, 2026, 1:10 a.m. |
| PD | Predicate disambiguation | batch_69a23fe3a87881909ab95bb3a0b474ec |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a240782e108190b6b60c26b84ae179 |
completed | Feb. 28, 2026, 1:10 a.m. |
Created at: Feb. 28, 2026, 12:54 a.m.