Triple
T21323400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rue de la Liberté |
E525681
|
entity |
| Predicate | hasSurroundingLandmarks |
P90437
|
FINISHED |
| Object | historic buildings of central Dijon |
—
|
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: historic buildings of central Dijon | Statement: [Rue de la Liberté, hasSurroundingLandmarks, historic buildings of central Dijon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurroundingLandmarks Context triple: [Rue de la Liberté, hasSurroundingLandmarks, historic buildings of central Dijon]
-
A.
typicalNearbyLandmarks
chosen
Indicates that certain landmarks are commonly found in the vicinity of a given place or location.
-
B.
isLocalLandmark
Indicates that something is recognized as a notable or significant landmark within a specific local area or community.
-
C.
hasNearbyLandUse
Indicates that one land area is located close to another area characterized by a specific type of land use.
-
D.
hasLandmarkArea
Indicates that a specified area is designated as the landmark area associated with a particular entity or location.
-
E.
isLandmarkFor
Indicates that one entity serves as a notable or significant reference point or attraction for another entity, such as a place, route, or area.
- 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_69e0b51ad810819098c12392c8e55f6c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e77ed572548190bd71ef690fc7befe |
completed | April 21, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69e6161feea4819091d13bb003363279 |
completed | April 20, 2026, 12:03 p.m. |
Created at: April 16, 2026, 4:40 p.m.