Triple
T31255608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noel Street |
E796956
|
entity |
| Predicate | hasMarketNearby |
P5648
|
FINISHED |
| Object | Berwick Street Market |
—
|
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: Berwick Street Market | Statement: [Noel Street, hasMarketNearby, Berwick Street Market]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMarketNearby Context triple: [Noel Street, hasMarketNearby, Berwick Street Market]
-
A.
hasInformalMarketNearby
Indicates that an entity is located close to an informal or unregulated market area.
-
B.
hasOutletNear
Indicates that one entity has a physical outlet or branch located in close proximity to another specified location or entity.
-
C.
hasNearbyCommercialFacilities
Indicates that a place is located close to one or more commercial facilities, such as shops, restaurants, or other businesses.
-
D.
hasNearbyFacility
chosen
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
E.
nearbyStateMarket
Indicates that a market is located in a state that is geographically close to the reference state.
- 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_69f224dd5fdc81908a4cd24917b67668 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a000a1d8fa88190a1d82ac746565c48 |
completed | May 10, 2026, 4:31 a.m. |
| PD | Predicate disambiguation | batch_6a0008b26eb88190ae03b2309a614774 |
completed | May 10, 2026, 4:25 a.m. |
Created at: April 29, 2026, 9:12 p.m.