Triple
T20138572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rae vald |
E491096
|
entity |
| Predicate | hasCapitalProximity |
P117282
|
FINISHED |
| Object | near Tallinn |
—
|
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: near Tallinn | Statement: [Rae vald, hasCapitalProximity, near Tallinn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCapitalProximity Context triple: [Rae vald, hasCapitalProximity, near Tallinn]
-
A.
isNearCapitalCity
chosen
Indicates that an entity is located close to, or in the immediate vicinity of, a capital city.
-
B.
hasDepartmentCapitalNearby
Indicates that the subject entity has a departmental capital city located in close geographical proximity to it.
-
C.
stateCapitalProximity
Indicates the spatial closeness or distance between a state’s capital city and another specified location.
-
D.
hasUrbanProximity
Indicates that one entity is located near or within easy access to an urban area associated with another entity.
-
E.
adjacentToProvinceCapital
Indicates that a location is directly next to or bordering the capital city of a province.
- 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_69da62651a0c8190a3e05e95e056a66b |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667698a188190869c18b925dba2ed |
completed | April 20, 2026, 5:50 p.m. |
| PD | Predicate disambiguation | batch_69e54cfb0d0081908e789b9b57e96668 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:32 p.m.