Triple
T20170391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snow Town (China Snow Town) |
E491942
|
entity |
| Predicate | typicalTravelSeason |
P13215
|
FINISHED |
| Object | December to February |
—
|
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: December to February | Statement: [Snow Town (China Snow Town), typicalTravelSeason, December to February]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTravelSeason Context triple: [Snow Town (China Snow Town), typicalTravelSeason, December to February]
-
A.
typicalSeasonTiming
chosen
Indicates the usual time period or season during which something normally occurs or is expected to take place.
-
B.
summerTouristSeason
Indicates the period during summer when a place experiences increased tourist activity or visitation.
-
C.
peakSeasonMonth
Indicates the month or months during which something (such as demand, activity, or occurrence) reaches its highest or most intense level.
-
D.
seasonalTourism
Indicates that tourism activity in a place varies significantly by season, with distinct peak and off-peak periods.
-
E.
typicalStartSeason
Indicates the season during which something (such as an activity, event, or phenomenon) usually begins.
- 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e66847ed9481908e6b23b399fa7005 |
completed | April 20, 2026, 5:54 p.m. |
| PD | Predicate disambiguation | batch_69e55b0c11cc8190836d1eee5945f000 |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:35 p.m.