Triple
T23658417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandhi Puja |
E584371
|
entity |
| Predicate | observedFrequency |
P146293
|
FINISHED |
| Object | annually |
—
|
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: annually | Statement: [Sandhi Puja, observedFrequency, annually]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: observedFrequency Context triple: [Sandhi Puja, observedFrequency, annually]
-
A.
canObserveFrequency
Indicates that one entity has the capability to detect, measure, or monitor the frequency of another entity or signal.
-
B.
encounterFrequency
chosen
Indicates how often two entities come into contact or interact with each other over a given period.
-
C.
observedFor
Indicates that one entity is monitored, watched, or examined over a period of time for the benefit or analysis of another entity.
-
D.
replacedFrequency
Indicates how often one entity is substituted for or takes the place of another over a given period.
-
E.
observedVia
Indicates that something is perceived, detected, or measured through a particular medium, instrument, method, or channel.
- 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_69e248ffc0888190ae23c4731eb8b7ac |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b35ce4bc81909a26bc7e44a929d8 |
completed | April 29, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69f118d7903c8190bb590a71771e93af |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:49 p.m.