Triple
T18737830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sri Padmavathi Ammavari Temple |
E458209
|
entity |
| Predicate | offersPrasadam |
P133355
|
FINISHED |
| Object | laddus |
—
|
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: laddus | Statement: [Sri Padmavathi Ammavari Temple, offersPrasadam, laddus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersPrasadam Context triple: [Sri Padmavathi Ammavari Temple, offersPrasadam, laddus]
-
A.
worshipersOffer
Indicates that worshipers present or dedicate offerings to a deity, sacred figure, or religious object.
-
B.
offersMeal
Indicates that one entity provides or makes available a meal to another entity.
-
C.
receivesOfferingsOf
Indicates that one entity is the recipient of offerings, tributes, or gifts presented by another entity.
-
D.
hasVotiveOfferings
Indicates that an entity possesses or is associated with votive offerings dedicated or presented in a religious or ritual context.
-
E.
offersFoodAndBeverage
Indicates that an entity provides both food and drink to another entity or for general consumption.
- 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_69d8d394dc308190b6725073f5db324c |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5768b80ac8190bc05628d64f86fc9 |
completed | April 20, 2026, 12:42 a.m. |
| PD | Predicate disambiguation | batch_69e48d03766c8190a43f7681842f4f8d |
completed | April 19, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e49a9bcc0c81908df3e513fd6762ff |
completed | April 19, 2026, 9:04 a.m. |
Created at: April 10, 2026, 11:51 a.m.