Triple
T23263129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince of Monaco |
E582064
|
entity |
| Predicate | territorySize |
P13411
|
FINISHED |
| Object | about 2 square kilometres |
—
|
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: about 2 square kilometres | Statement: [Prince of Monaco, territorySize, about 2 square kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: territorySize Context triple: [Prince of Monaco, territorySize, about 2 square kilometres]
-
A.
territoryType
Indicates the specific kind or classification of a territory associated with an entity (e.g., country, region, zone, or jurisdiction type).
-
B.
territorialExtent
Indicates the geographic area or spatial range over which something extends, applies, or has jurisdiction.
-
C.
hasLargeTerritory
Indicates that an entity occupies or controls a geographically extensive area relative to typical or comparable entities.
-
D.
areaTotalSquareKilometers
chosen
Indicates the total size of something measured in square kilometers.
-
E.
hasLandAreaRange
Indicates that an entity’s land area falls within a specified minimum-to-maximum range.
- 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_69e246079f58819085eaa9c260906880 |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f194caaf208190931923744692180d |
completed | April 29, 2026, 5:19 a.m. |
| PD | Predicate disambiguation | batch_69effce4d704819092826931d430e8c4 |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:11 p.m.