Triple
T38427125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Rosario monarch sanctuary |
E903390
|
entity |
| Predicate | tourismPeakMonths |
P108895
|
FINISHED |
| Object | December |
—
|
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 | Statement: [El Rosario monarch sanctuary, tourismPeakMonths, December]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourismPeakMonths Context triple: [El Rosario monarch sanctuary, tourismPeakMonths, December]
-
A.
peakSeasonMonth
chosen
Indicates the month or months during which something (such as demand, activity, or occurrence) reaches its highest or most intense level.
-
B.
isPeakVacationMonthIn
Indicates that a given month falls within the period of highest typical vacation activity in a specified location or context.
-
C.
seasonalTourism
Indicates that tourism activity in a place varies significantly by season, with distinct peak and off-peak periods.
-
D.
hasPeakVisitationSeason
Indicates that an entity experiences its highest or most concentrated level of visitation during a specific season or time period.
-
E.
bestHikingMonths
Indicates the months of the year during which hiking conditions are considered most favorable for a given place or trail.
- 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_69f76e67e4fc8190a7d08dfe9a8af998 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcd1499e2c81909bafd84dc4810f45 |
completed | May 7, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69fcccf024ec819086383ffbb6cfc036 |
completed | May 7, 2026, 5:33 p.m. |
Created at: May 3, 2026, 4:31 p.m.