Triple
T8460822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shivini |
E200033
|
entity |
| Predicate | receivesOffering |
P82772
|
FINISHED |
| Object | sacrifices |
—
|
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: sacrifices | Statement: [Shivini, receivesOffering, sacrifices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: receivesOffering Context triple: [Shivini, receivesOffering, sacrifices]
-
A.
hasOffering
Indicates that one entity provides, presents, or makes available an offering (such as a product, service, or item) to another entity or context.
-
B.
offering
Indicates that one entity presents or provides something to another entity, typically as a gift, contribution, or proposal.
-
C.
offeringOutcome
Indicates the result or consequence that follows from making a particular offering.
-
D.
usesOffering
Indicates that one entity makes use of, applies, or relies on a particular offering provided by another entity.
-
E.
usedAsOfferingAt
Indicates that something is employed or presented as an offering in a particular context, place, or event.
- 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_69ca83198c4c8190a337bf717d1813f5 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe49fca788190a8728ff74f4d26f5 |
completed | March 31, 2026, 3:13 p.m. |
| PD | Predicate disambiguation | batch_69cbd0fc634481909842c0a30077bfde |
completed | March 31, 2026, 1:49 p.m. |
| PDg | Predicate description generation | batch_69cbe12dd0b88190a38ec4d15dcc870b |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 6:10 p.m.