Triple
T911412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Lake |
E19665
|
entity |
| Predicate | neighborhoodType |
P19245
|
FINISHED |
| Object | residential neighborhood |
—
|
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 neighborhood | Statement: [The Lake, neighborhoodType, residential neighborhood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: neighborhoodType Context triple: [The Lake, neighborhoodType, residential neighborhood]
-
A.
notableNeighborhoodType
chosen
Indicates that a neighborhood is notably characterized by, or strongly associated with, a particular type or category (e.g., residential, commercial, historic).
-
B.
neighborhood
Indicates that one entity is located in close spatial proximity to another, typically within the same local area or district.
-
C.
neighborhoodCharacteristic
Indicates that a particular characteristic, feature, or quality is associated with or describes a given neighborhood.
-
D.
hasNeighbourhood
Indicates that one entity is located within, or is associated with, a particular neighborhood area of another entity.
-
E.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
- 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_69a4939f91a08190ba68c2c81eab90fe |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2f605bc8190a5245aa2ca55cf43 |
completed | March 1, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69a4b2918ea881908698020b995a8eae |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:39 p.m.