Triple
T4162131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glycine max |
E91553
|
entity |
| Predicate | primaryUseInFeed |
P54188
|
FINISHED |
| Object | protein source for livestock |
—
|
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: protein source for livestock | Statement: [Glycine max, primaryUseInFeed, protein source for livestock]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryUseInFeed Context triple: [Glycine max, primaryUseInFeed, protein source for livestock]
-
A.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
B.
primaryMode
Indicates the main or most commonly used method, manner, or form in which an action, process, or interaction is carried out between entities.
-
C.
primaryContent
Indicates that one entity serves as the main or most important content associated with another entity.
-
D.
primaryServes
Indicates that one entity’s main or principal function is to serve, support, or provide service to another entity.
-
E.
primaryInterest
Indicates that one entity is the main or most significant focus of attention, concern, or engagement for another entity.
- 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_69aed9626ebc8190a39de631788bea3e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0321eee88190871c1d4bf44a5007 |
completed | March 9, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69af018dc90c8190a754b1bfbc802e80 |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af0320775c8190b90d80f512060f1c |
completed | March 9, 2026, 5:28 p.m. |
Created at: March 9, 2026, 3:44 p.m.