Triple
T4811839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Marino Historic Centre and Mount Titano |
E107085
|
entity |
| Predicate | bufferZoneHectares |
P59766
|
FINISHED |
| Object | 167 |
—
|
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: 167 | Statement: [San Marino Historic Centre and Mount Titano, bufferZoneHectares, 167]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bufferZoneHectares Context triple: [San Marino Historic Centre and Mount Titano, bufferZoneHectares, 167]
-
A.
areaApproxKm2
Indicates that one entity has an approximate area, measured in square kilometers, given by the other entity.
-
B.
landArea
Indicates the total surface area of a piece of land associated with an entity, typically measured in standardized units (e.g., square meters, hectares).
-
C.
areaTotalSquareKilometers
Indicates the total size of something measured in square kilometers.
-
D.
forestArea
Indicates the extent or size of land covered by forest within a given area or region.
-
E.
hasNumberOfAcres
Indicates the specific quantity of land area, measured in acres, that is associated with an entity.
- F. None of above. chosen
Provenance (4 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_69bd43f779448190b92885cb70abb6c2 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1dfa3481909d240d50ed0ee38c |
completed | March 20, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69bd6dda5e808190a26ec85e4499d8e4 |
completed | March 20, 2026, 3:55 p.m. |
Created at: March 20, 2026, 1:23 p.m.