Triple
T26139943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sparks Street |
E659488
|
entity |
| Predicate | isDowntownShoppingArea |
P120873
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Sparks Street, isDowntownShoppingArea, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isDowntownShoppingArea Context triple: [Sparks Street, isDowntownShoppingArea, yes]
-
A.
isShoppingDistrict
chosen
Indicates that a location functions primarily as a shopping district, characterized by a concentration of retail stores and commercial shopping activity.
-
B.
hasShoppingDistrict
Indicates that a place contains or is associated with a designated area where multiple shops and commercial retail activities are concentrated.
-
C.
hasDowntownCharacteristic
Indicates that something possesses a feature, quality, or attribute typically associated with a downtown area.
-
D.
isDowntownHub
Indicates that a location functions as a central, primary hub within a city’s downtown area.
-
E.
hasShoppingDistrictType
Indicates that an entity is associated with a particular type or category of shopping district.
- 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_69ee5bc3c20c8190bf2cf272f4170e95 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f60be435b48190a389ebb5a4537a16 |
completed | May 2, 2026, 2:36 p.m. |
| PD | Predicate disambiguation | batch_69f5b0021da88190bdd4cf2698c23edf |
completed | May 2, 2026, 8:04 a.m. |
Created at: April 26, 2026, 8:19 p.m.