Triple
T3789729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katoomba |
E89614
|
entity |
| Predicate | occasionallyExperiences |
P47451
|
FINISHED |
| Object | snowfalls in winter |
—
|
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: snowfalls in winter | Statement: [Katoomba, occasionallyExperiences, snowfalls in winter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occasionallyExperiences Context triple: [Katoomba, occasionallyExperiences, snowfalls in winter]
-
A.
experiences
Indicates that an entity undergoes, feels, or is affected by a particular event, state, or condition.
-
B.
occasionalRange
chosen
Indicates that the relationship or action occurs intermittently or at irregular intervals within a specified range or context.
-
C.
frequentOccasion
Indicates that a particular event, situation, or condition occurs repeatedly or commonly over time.
-
D.
typicallySpared
Indicates that an entity is usually not affected by, excluded from, or left untouched by a particular action, process, or condition.
-
E.
oftenAccompaniedBy
Indicates that one entity is frequently found together with, occurs alongside, or is commonly associated in presence or use with another entity.
- 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_69aed9597d6881909b6ee3b9de859223 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeecefa3608190a7a20ed6df6a64b2 |
completed | March 9, 2026, 3:53 p.m. |
| PD | Predicate disambiguation | batch_69aee743c8d08190a9f9c97b836bd703 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:15 p.m.