Triple
T21998352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finance Bill (India) |
E543261
|
entity |
| Predicate | introducedFrequency |
P513
|
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: [Finance Bill (India), introducedFrequency, annually]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedFrequency Context triple: [Finance Bill (India), introducedFrequency, annually]
-
A.
usesFrequency
Indicates that one entity employs or operates another entity at a specified rate, interval, or number of occurrences over time.
-
B.
notableFrequency
Indicates that an action, event, or occurrence happens with a frequency that is significant or noteworthy compared to typical expectations.
-
C.
introduced
chosen
Indicates that one entity caused another entity to become known, presented, or brought into use for the first time to a person, group, or context.
-
D.
isFrequently
Indicates that an action, state, or relationship occurs often or with high regularity between the related entities.
-
E.
replacedFrequency
Indicates how often one entity is substituted for or takes the place of another over a given period.
- 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_69e11e2c814c8190837d072789000486 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1276774508190b96870266e10979a |
completed | April 28, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69e6f62dc9d88190ae387f145f9528de |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:19 p.m.