Triple
T3142854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Newcastle Beach |
E65692
|
entity |
| Predicate | hasCityCentreProximity |
P34630
|
FINISHED |
| Object | close to Newcastle city centre |
—
|
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: close to Newcastle city centre | Statement: [Newcastle Beach, hasCityCentreProximity, close to Newcastle city centre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCityCentreProximity Context triple: [Newcastle Beach, hasCityCentreProximity, close to Newcastle city centre]
-
A.
hasCityCentreLocation
Indicates that something is located in, or directly associated with, the central area of a city.
-
B.
hasUrbanProximity
Indicates that one entity is located near or within easy access to an urban area associated with another entity.
-
C.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
D.
administrativeCentreNearby
Indicates that an administrative centre is located close to the referenced entity in geographic or spatial terms.
-
E.
nearDowntown
chosen
Indicates that one location is situated close to or within a short distance of a city’s downtown 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_69ad8582f564819088c27e1f96153938 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada579b07c8190a7b316f499911a2d |
completed | March 8, 2026, 4:36 p.m. |
| PD | Predicate disambiguation | batch_69ad9df840088190a26a1516f4c1f056 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:05 p.m.