Triple
T34167002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La France pears |
E876438
|
entity |
| Predicate | ripeningCharacteristic |
P18450
|
FINISHED |
| Object | ripens off the tree |
—
|
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: ripens off the tree | Statement: [La France pears, ripeningCharacteristic, ripens off the tree]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ripeningCharacteristic Context triple: [La France pears, ripeningCharacteristic, ripens off the tree]
-
A.
ripeningTime
Indicates the period or duration required for something to become fully ripe or reach its mature, ready-to-use state.
-
B.
ripenedUsing
Indicates that something has undergone a ripening process by means of, or with the help of, a specified agent, method, or substance.
-
C.
ripeningTimeRelative
Indicates the temporal relationship between this entity’s ripening period and a reference ripening period (e.g., earlier, later, or at the same time).
-
D.
fruitCharacteristic
chosen
Indicates that a specified characteristic or property is attributed to a particular fruit.
-
E.
cheeseRipeningStyle
Indicates the method or process by which a cheese is matured or aged to develop its flavor and texture.
- 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_69f349ad97ac8190bf1f17417c970e64 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f70fdfb02481908656f80d4f801ddf |
completed | May 3, 2026, 9:05 a.m. |
| PD | Predicate disambiguation | batch_69f70f3c5bfc81908585f52e196dafe5 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:54 a.m.