Triple
T867456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sudama |
E18735
|
entity |
| Predicate | bringsGift |
P2329
|
FINISHED |
| Object | flattened rice (poha) for Krishna |
—
|
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: flattened rice (poha) for Krishna | Statement: [Sudama, bringsGift, flattened rice (poha) for Krishna]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bringsGift Context triple: [Sudama, bringsGift, flattened rice (poha) for Krishna]
-
A.
traditionalGift
Indicates that one entity customarily gives another entity a gift in accordance with established traditions or cultural practices.
-
B.
givenFor
Indicates that something is provided, offered, or assigned in favor of or on behalf of a particular entity or purpose.
-
C.
givenTo
chosen
Indicates that something is transferred or presented by one entity to another as a recipient.
-
D.
hasGiftShop
Indicates that an entity includes or provides access to a gift shop as part of its facilities or services.
-
E.
carriedBy
Indicates that one entity is physically supported and transported by another entity.
- 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_69a4938ce8688190a24bdfef82ba7d21 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac7e12b0819084d25b9a66888a91 |
completed | March 1, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69a4aa87504481909618a6815948da6f |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.