Triple
T34391319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Nicola Arcella |
E882708
|
entity |
| Predicate | hasNaturalLandmark |
P1094
|
FINISHED |
| Object | sea arch Arco Magno |
—
|
NE NERFINISHED |
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: sea arch Arco Magno | Statement: [San Nicola Arcella, hasNaturalLandmark, sea arch Arco Magno]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNaturalLandmark Context triple: [San Nicola Arcella, hasNaturalLandmark, sea arch Arco Magno]
-
A.
hasNaturalFeature
chosen
Indicates that one entity possesses, contains, or is characterized by a particular natural feature (such as a mountain, river, forest, or coastline).
-
B.
isNaturalFeature
Indicates that the subject is a naturally occurring physical feature of the environment, not created or significantly altered by human activity.
-
C.
naturalAttractionOf
Indicates a relationship where one entity is a natural feature or site that draws interest, attention, or visitors from another entity.
-
D.
hasLandform
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
-
E.
hasLandmarkProperty
Indicates that something possesses a notable or defining landmark-related characteristic or feature.
- 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_69f349c1304081909331872829e38106 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff0d80c0dc81909fbd12285c7a45c0 |
completed | May 9, 2026, 10:33 a.m. |
| PD | Predicate disambiguation | batch_69ff0cd03e78819094895058f925fbfa |
completed | May 9, 2026, 10:30 a.m. |
Created at: May 1, 2026, 1:59 a.m.