Triple
T3565359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Market Street and Castro Street |
E75433
|
entity |
| Predicate | nearbyCommercialUse |
P19783
|
FINISHED |
| Object | restaurants |
—
|
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: restaurants | Statement: [Market Street and Castro Street, nearbyCommercialUse, restaurants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyCommercialUse Context triple: [Market Street and Castro Street, nearbyCommercialUse, restaurants]
-
A.
hasNearbyLandUse
chosen
Indicates that one land area is located close to another area characterized by a specific type of land use.
-
B.
nearbyVenue
Indicates that one venue is located close to another venue in physical space.
-
C.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
D.
commercialArea
Indicates that the location or region is designated primarily for commercial activities such as businesses, shops, or services.
-
E.
hasNearbyFacility
Indicates that one entity is located close to or in the vicinity of a particular facility.
- 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_69ad85d512708190829c8b2d3a2ccfb8 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0a8f6288190928479f5bea32245 |
completed | March 8, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69adb834779081908468e182d5f6cf02 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:21 p.m.