Triple
T29661701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingswell Camera Shop |
E750424
|
entity |
| Predicate | areaOfPark |
P168772
|
FINISHED |
| Object | Buena Vista Street shopping district |
—
|
NE NERFINISHED |
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: Buena Vista Street shopping district | Statement: [Kingswell Camera Shop, areaOfPark, Buena Vista Street shopping district]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaOfPark Context triple: [Kingswell Camera Shop, areaOfPark, Buena Vista Street shopping district]
-
A.
parkArea
Indicates that an area of land is designated and used as a park or recreational green space.
-
B.
hasParkArea
Indicates that an entity includes or is associated with a designated park or recreational area within its boundaries.
-
C.
regionOfPark
Indicates that one entity is a geographic or administrative region that contains or is designated as a specific park.
-
D.
largestParkArea
Indicates that, among a set of entities, one has the park whose area is greater than or equal to that of any other entity’s park.
-
E.
parkAreaType
Indicates the classification of a park’s area according to its designated type or functional category.
- 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_69f0d62418a08190a401b127adf9f8a6 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f67805551c81909e016ae9e3031076 |
completed | May 2, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69f675ff62c48190a634bbb8896973b9 |
completed | May 2, 2026, 10:09 p.m. |
| PDg | Predicate description generation | batch_69f676f73c3481909f01fa69851b7298 |
completed | May 2, 2026, 10:13 p.m. |
Created at: April 28, 2026, 6:58 p.m.