Triple
T12770884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Radha Kund |
E305243
|
entity |
| Predicate | hasReligiousRitual |
P4193
|
FINISHED |
| Object | offering lamps on water |
—
|
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: offering lamps on water | Statement: [Radha Kund, hasReligiousRitual, offering lamps on water]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousRitual Context triple: [Radha Kund, hasReligiousRitual, offering lamps on water]
-
A.
hasRituals
Indicates that one entity performs, observes, or is associated with specific rituals in relation to another entity or context.
-
B.
hasRitual
chosen
Indicates that an entity performs, observes, or is associated with a specific ritual or ceremonial practice.
-
C.
hasLifecycleRitual
Indicates that an entity is associated with a ritual or ceremonial practice marking a significant stage or transition in its lifecycle.
-
D.
ritualActivities
Indicates that one entity engages in, performs, or is associated with ritualistic or ceremonial activities in relation to another entity or context.
-
E.
languageUsedInRituals
Indicates that a particular language is employed as the medium of speech, chant, or recitation during specific rituals or ceremonial practices.
- 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96df4b36c81909bcc913dd5e535f8 |
completed | April 10, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69d96409739881909174ba005a986cb5 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:28 p.m.