Triple
T9824237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marina Piccola |
E238612
|
entity |
| Predicate | hasSunExposure |
P81429
|
FINISHED |
| Object | strong midday sun |
—
|
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 midday sun | Statement: [Marina Piccola, hasSunExposure, strong midday sun]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSunExposure Context triple: [Marina Piccola, hasSunExposure, strong midday sun]
-
A.
hasSolarRadiation
chosen
Indicates that an entity is subject to, receives, or is characterized by a certain amount or presence of solar radiation.
-
B.
sunRequirement
Indicates the amount or type of sunlight an entity (such as a plant or object) needs or is designed to receive.
-
C.
hasExposuresIn
Indicates that an entity is subject to or involved in certain risks, conditions, or influencing factors within a specified context, environment, or domain.
-
D.
photosensitivity
Indicates a relationship where an entity reacts or responds in a particular way when exposed to light.
-
E.
hasMinimumSolarInsolation
Indicates that an entity receives at least a specified minimum amount of solar energy (insolation) over a given area and time period.
- 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_69ca84e0dd1881909800765d1e21f735 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb316f8948190ada3738787a5cb6a |
completed | April 2, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cd03e01ea881909a7d93fc3994ace5 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:31 p.m.