Triple
T18492660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tulum Valley |
E451854
|
entity |
| Predicate | sunshineHours |
P57952
|
FINISHED |
| Object | high annual sunshine |
—
|
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: high annual sunshine | Statement: [Tulum Valley, sunshineHours, high annual sunshine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sunshineHours Context triple: [Tulum Valley, sunshineHours, high annual sunshine]
-
A.
sunshineHoursPerYear
chosen
Indicates the total number of hours in a year during which a location receives direct sunshine.
-
B.
averageAnnualSunshineDays
Indicates the typical number of days per year that a location experiences sunshine, averaged over a specified period.
-
C.
hasMaximumSolarInsolation
Indicates that an entity receives the highest level of solar radiation or sunlight intensity compared to relevant alternatives or within a given context.
-
D.
hasSolarRadiation
Indicates that an entity is subject to, receives, or is characterized by a certain amount or presence of solar radiation.
-
E.
sunRequirement
Indicates the amount or type of sunlight an entity (such as a plant or object) needs or is designed to receive.
- 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_69d8d3855d50819097fc8561b0299dd9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e532be5e988190aae93a66f6e5f857 |
completed | April 19, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69e469d671088190b619de96ea6f92ab |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:35 a.m.