Triple
T4854907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atlantic Avenue (Brooklyn) |
E108512
|
entity |
| Predicate | hasLandUseMix |
P43475
|
FINISHED |
| Object | residential |
—
|
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: residential | Statement: [Atlantic Avenue (Brooklyn), hasLandUseMix, residential]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandUseMix Context triple: [Atlantic Avenue (Brooklyn), hasLandUseMix, residential]
-
A.
hasUrbanRuralMix
Indicates that something exhibits a combination or blend of both urban and rural characteristics or components.
-
B.
hasLandUseCharacter
chosen
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
-
C.
hasLandOwnershipMix
Indicates that an entity has a particular combination or distribution of different types of land ownership (e.g., public, private, communal) associated with it.
-
D.
landUseIncludes
Indicates that a specified land area contains or permits the specified type(s) of land use within its boundaries.
-
E.
hasNearbyLandUse
Indicates that one land area is located close to another area characterized by a specific type of land use.
- 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_69bd440a89548190a5f14ba6da6b97dc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2557388190a2d15571bacd24f3 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:26 p.m.