Triple
T13620465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sovereign Prince of Monaco |
E325434
|
entity |
| Predicate | territorySizeOfRealm |
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: [Sovereign Prince of Monaco, territorySizeOfRealm, about 2 square kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: territorySizeOfRealm Context triple: [Sovereign Prince of Monaco, territorySizeOfRealm, about 2 square kilometres]
-
A.
realmRuled
Indicates that one entity serves as the sovereign or governing ruler over a particular realm, territory, or domain.
-
B.
areaTotalSquareKilometers
chosen
Indicates the total size of something measured in square kilometers.
-
C.
hasLandAreaRange
Indicates that an entity’s land area falls within a specified minimum-to-maximum range.
-
D.
territorialExtent
Indicates the geographic area or spatial range over which something extends, applies, or has jurisdiction.
-
E.
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).
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae1b3ee481909bd43ded6227a3e5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:50 p.m.