Triple
T8667176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philippine Rice Research Institute (Los Baños stations) |
E205704
|
entity |
| Predicate | focusesOnCrop |
P31
|
FINISHED |
| Object | Oryza sativa |
—
|
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: Oryza sativa | Statement: [Philippine Rice Research Institute (Los Baños stations), focusesOnCrop, Oryza sativa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusesOnCrop Context triple: [Philippine Rice Research Institute (Los Baños stations), focusesOnCrop, Oryza sativa]
-
A.
usesCrop
Indicates that one entity employs or applies a particular crop for a specific purpose or function.
-
B.
focusesOn
chosen
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
C.
notableCrop
Indicates that a particular crop is especially significant, prominent, or characteristic in relation to the referenced entity.
-
D.
includesCrop
Indicates that one entity (such as a field, farm, or agricultural area) contains or has within it a specified crop.
-
E.
includesCropType
Indicates that an entity contains or encompasses a specific type of crop within its scope or composition.
- 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_69ca83516ae88190aefe034b3bc589e3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc48a34b808190aa9aed9cdb2900e6 |
completed | March 31, 2026, 10:20 p.m. |
| PD | Predicate disambiguation | batch_69cc4564e018819081036722f3e42a71 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:31 p.m.