Triple
T27267904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bay Terrace, Staten Island |
E687955
|
entity |
| Predicate | hasRetailCluster |
P25135
|
FINISHED |
| Object | shopping plazas along Hylan Boulevard |
—
|
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: shopping plazas along Hylan Boulevard | Statement: [Bay Terrace, Staten Island, hasRetailCluster, shopping plazas along Hylan Boulevard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRetailCluster Context triple: [Bay Terrace, Staten Island, hasRetailCluster, shopping plazas along Hylan Boulevard]
-
A.
hasRetailPresenceIn
Indicates that an entity conducts retail operations or maintains a retail outlet, store, or sales presence within a specified location.
-
B.
hasRetailCenters
Indicates that an entity possesses, operates, or is associated with one or more retail centers.
-
C.
hasRetailNetwork
Indicates that an entity operates or is associated with a system of retail outlets or distribution channels through which products or services are sold.
-
D.
hasRetailStores
Indicates that an entity operates or possesses one or more physical retail store locations.
-
E.
hasRetailArea
chosen
Indicates that an entity possesses or includes a designated space used for retail or commercial sales activities.
- 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_69ef3557abc481908bf3c146f0f3356a |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69fe991bca608190b524e419642f4243 |
completed | May 9, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69fe979fc1c4819091fc48d63ea12063 |
completed | May 9, 2026, 2:10 a.m. |
Created at: April 27, 2026, 10:57 a.m.