Triple
T30586869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oryza schlechteri |
E778537
|
entity |
| Predicate | ofInterestFor |
P25176
|
FINISHED |
| Object | agricultural research |
—
|
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: agricultural research | Statement: [Oryza schlechteri, ofInterestFor, agricultural research]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ofInterestFor Context triple: [Oryza schlechteri, ofInterestFor, agricultural research]
-
A.
subjectInterest
Indicates that the subject has an interest in, or is concerned with, the object.
-
B.
interestMayBe
Indicates that one entity potentially has an interest in, or may be interested in, another entity or subject.
-
C.
collectorInterest
Indicates that one entity has a special interest in acquiring, owning, or seeking out another entity as part of a collection.
-
D.
recognizedInterest
Indicates that one entity has formally acknowledged or identified another entity’s interest in something as valid or relevant.
-
E.
hasAreaOfInterest
chosen
Indicates that an entity possesses or is associated with a particular area of interest or focus.
- 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_69f224a04b248190b0ca443ec86207b8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68977c2148190bc9679fdc90ff482 |
completed | May 2, 2026, 11:32 p.m. |
| PD | Predicate disambiguation | batch_69f67e42d6688190b60e91d2c388c555 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 29, 2026, 8:23 p.m.