Triple
T19927266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Didube |
E478956
|
entity |
| Predicate | hasCommercialStallsNearby |
P4285
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Didube, hasCommercialStallsNearby, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommercialStallsNearby Context triple: [Didube, hasCommercialStallsNearby, true]
-
A.
isCommercialFacility
Indicates that a facility is used primarily for commercial or business-related activities or services.
-
B.
hasShoppingDistrict
chosen
Indicates that a place contains or is associated with a designated area where multiple shops and commercial retail activities are concentrated.
-
C.
connectsToCommercialArea
Indicates that one location has a direct link, route, or access path to a commercial area.
-
D.
isShoppingDistrict
Indicates that a location functions primarily as a shopping district, characterized by a concentration of retail stores and commercial shopping activity.
-
E.
hasShopsOn
Indicates that one entity (typically a street, area, or building) contains or is lined with shops located on or along it.
- 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659ca52c881908dc8053bf61be4c4 |
completed | April 20, 2026, 4:52 p.m. |
| PD | Predicate disambiguation | batch_69e537f070b481908958e0e5911dcdc1 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:53 p.m.