Triple
T1802398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oryza sativa |
E39749
|
entity |
| Predicate | isStapleFoodFor |
P17103
|
FINISHED |
| Object | over half of the world population |
—
|
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: over half of the world population | Statement: [Oryza sativa, isStapleFoodFor, over half of the world population]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isStapleFoodFor Context triple: [Oryza sativa, isStapleFoodFor, over half of the world population]
-
A.
hasStapleFood
Indicates that an entity’s primary or regularly consumed basic food item is another specified entity.
-
B.
primaryFood
chosen
Indicates that one entity serves as the main or most important food source for another entity.
-
C.
servesDish
Indicates that one entity prepares and presents a specific dish as food for another entity.
-
D.
feedingStructure
Indicates a relationship where one entity serves as the anatomical or mechanical structure used by another entity to obtain or ingest food.
-
E.
mayBeGivenTo
Indicates that something is permitted or eligible to be transferred, assigned, or provided from one entity to another.
- 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_69a88632aa588190ba3978fde0db5bbd |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aba67721788190951beae25e885457 |
completed | March 7, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69aa61d514c081908197ac1f7c7d7a88 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:32 p.m.