Triple
T38051313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Recto Avenue |
E949766
|
entity |
| Predicate | hasNearbyAreaType |
P115275
|
FINISHED |
| Object | densely populated urban area |
—
|
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: densely populated urban area | Statement: [Recto Avenue, hasNearbyAreaType, densely populated urban area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyAreaType Context triple: [Recto Avenue, hasNearbyAreaType, densely populated urban area]
-
A.
hasNearbySiteType
Indicates that one entity has another entity of a specified site type located in its close physical vicinity.
-
B.
hasNearbyGeographicalArea
Indicates that one geographical area is located in close spatial proximity to another geographical area.
-
C.
hasNearbyInfrastructureType
Indicates that an entity is located close to infrastructure of a specified type.
-
D.
hasNearbyPropertyType
chosen
Indicates that one entity has another entity of a specified property type located in close physical proximity to it.
-
E.
hasNearbyTownType
Indicates that one entity has, in its vicinity, a town of a specified type or classification.
- 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_69f76f000cf081908c11fb5443b392e6 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a00bb3a6f888190b3ecd0fbc9af9b4a |
completed | May 10, 2026, 5:07 p.m. |
| PD | Predicate disambiguation | batch_6a00b902dbf881909e098ff102b7ea7e |
completed | May 10, 2026, 4:57 p.m. |
Created at: May 3, 2026, 4:20 p.m.