Triple
T23603154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sol de Mañana geyser field |
E582814
|
entity |
| Predicate | reasonForBestVisitTime |
P41485
|
FINISHED |
| Object | strong contrast between cold air and hot steam |
—
|
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: strong contrast between cold air and hot steam | Statement: [Sol de Mañana geyser field, reasonForBestVisitTime, strong contrast between cold air and hot steam]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForBestVisitTime Context triple: [Sol de Mañana geyser field, reasonForBestVisitTime, strong contrast between cold air and hot steam]
-
A.
bestTimeOfDayToVisit
Indicates the time of day during which visiting something is considered most optimal or desirable.
-
B.
popularTimeToVisit
Indicates the time period during which a place is most frequently visited or experiences peak visitor activity.
-
C.
reasonForTime
chosen
Indicates that one entity provides the explanation or cause for a particular point or duration of time associated with another entity.
-
D.
bestTimeToExperience
Indicates the optimal or most favorable time period during which an entity should be experienced or enjoyed.
-
E.
reasonForAppointment
Indicates the underlying purpose or cause for which an appointment is scheduled or taking place.
- 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_69e248faa2788190abb1581742daa6aa |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b095410481908446f44c402f9dc7 |
completed | April 29, 2026, 7:17 a.m. |
| PD | Predicate disambiguation | batch_69f118c96a0081908a8ac98ef7e7e60c |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:43 p.m.