Triple
T7337938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moore neighborhood |
E169176
|
entity |
| Predicate | spaceType |
P77125
|
FINISHED |
| Object | discrete space |
—
|
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: discrete space | Statement: [Moore neighborhood, spaceType, discrete space]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spaceType Context triple: [Moore neighborhood, spaceType, discrete space]
-
A.
typeOfBuildingSpace
Indicates the specific kind or category of building space that an entity represents or occupies.
-
B.
performanceSpaceType
Indicates the specific kind or category of space in which a performance or event takes place.
-
C.
openSpaceType
Indicates the type or category of an open space associated with an entity (e.g., park, plaza, courtyard).
-
D.
buildingType
Indicates the specific category or function that characterizes what kind of building something is.
-
E.
associatedSpaceFacility
Indicates that there is a relationship linking an entity to a specific space-related facility with which it is connected or involved.
- F. None of above. chosen
Provenance (4 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_69c68a57710481909f0c1f3c6ebdb6f2 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f347f25081908e6086d4073295f5 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f028fd748190b2ea5c3081958a42 |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f3463d0481908aed9ed43a8ac6a8 |
completed | March 27, 2026, 9:14 p.m. |
Created at: March 27, 2026, 3:04 p.m.