Triple
T8773195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kerala Legislative Assembly |
E208513
|
entity |
| Predicate | winterSession |
P85319
|
FINISHED |
| Object | held 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: held annually | Statement: [Kerala Legislative Assembly, winterSession, held annually]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winterSession Context triple: [Kerala Legislative Assembly, winterSession, held annually]
-
A.
winterStatus
Indicates the condition, phase, or circumstances associated with the winter season for a given entity or context.
-
B.
winterFrequency
Indicates how often the related event, condition, or phenomenon occurs during the winter season.
-
C.
summerWinterCycle
Indicates a recurring transition between summer and winter seasons, capturing the cyclical change in conditions or states across these two periods.
-
D.
winterCharacteristic
Indicates a characteristic, feature, or quality that is specifically associated with or typical of winter.
-
E.
winterAscentFirstBy
Indicates that the referenced ascent is the first successful climb of a route, peak, or face carried out specifically in winter conditions by the specified climber or party.
- 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_69ca835edb4481909b4aafb616dc5eb7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f2dc87c8190be0597a260d95a0b |
completed | March 31, 2026, 11:56 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1aff3881908be6a9cbc9f50461 |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5cfddef48190aee764ee7b25bae9 |
completed | March 31, 2026, 11:47 p.m. |
Created at: March 30, 2026, 6:41 p.m.