Triple
T19103376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annaprasadam (free meals) department |
E467590
|
entity |
| Predicate | costToBeneficiary |
P5902
|
FINISHED |
| Object | free of charge |
—
|
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: free of charge | Statement: [Annaprasadam (free meals) department, costToBeneficiary, free of charge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: costToBeneficiary Context triple: [Annaprasadam (free meals) department, costToBeneficiary, free of charge]
-
A.
costToUser
chosen
Indicates the amount of cost or expense that is borne by, charged to, or incurred by the user.
-
B.
costSharing
Indicates how the financial burden of a cost is divided or shared among multiple parties.
-
C.
beneficiaryContribution
Indicates that one party provides a contribution, support, or resources that benefit another designated beneficiary.
-
D.
costarWith
Indicates that two performers appear together as significant cast members in the same production, such as a film, television show, or stage performance.
-
E.
chargeBasis
Indicates the underlying reason, justification, or legal/contractual basis on which a charge, fee, or accusation is applied.
- 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e36f84048190a62c52411eb55411 |
completed | April 20, 2026, 8:27 a.m. |
| PD | Predicate disambiguation | batch_69e4b9ac41848190afd0f33b42cebe99 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:04 p.m.