Triple
T714778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elaeagnaceae |
E14288
|
entity |
| Predicate | fruitCharacteristic |
P18450
|
FINISHED |
| Object | often fleshy fruit |
—
|
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: often fleshy fruit | Statement: [Elaeagnaceae, fruitCharacteristic, often fleshy fruit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fruitCharacteristic Context triple: [Elaeagnaceae, fruitCharacteristic, often fleshy fruit]
-
A.
flowerCharacteristic
Indicates that a flower possesses a particular attribute, quality, or feature (such as color, shape, size, or scent).
-
B.
wineCharacteristic
Indicates a descriptive property or quality attributed to a wine, such as its flavor, aroma, color, or style.
-
C.
fruitCommonName
Indicates the commonly used everyday name by which a fruit is known.
-
D.
viticulturalCharacteristic
Indicates a relationship where a specific trait, quality, or property is attributed to viticulture or grape-growing practices.
-
E.
nationalFruit
Indicates that a particular fruit is officially designated as the national fruit of a country or region.
- 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_69a4934a36e081909e7abef98b898a4e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5738e04819082eac673b3b7c4c2 |
completed | March 1, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f38898819089d79bad4f4ff2d2 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a57267c481909790a1fda3fced08 |
completed | March 1, 2026, 8:45 p.m. |
Created at: March 1, 2026, 7:36 p.m.