Triple
T17195963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Circus |
E417350
|
entity |
| Predicate | hasNearbyStreetPattern |
P126682
|
FINISHED |
| Object | radiating streets |
—
|
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: radiating streets | Statement: [The Circus, hasNearbyStreetPattern, radiating streets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyStreetPattern Context triple: [The Circus, hasNearbyStreetPattern, radiating streets]
-
A.
hasNearbyStreet
Indicates that one entity is located close to or adjacent to a street.
-
B.
hasConnectingStreet
Indicates that two locations are linked by a street that directly connects them.
-
C.
hasStreetNamingPattern
Indicates that there is a characteristic or systematic way in which streets are named in relation to a given entity.
-
D.
hasStreetGridPattern
Indicates that an area’s street layout follows a structured, grid-like pattern of intersecting roads.
-
E.
hasSideStreetType
Indicates that an entity (such as a street or road segment) is associated with a specific type or classification of side street.
- F. None of above. chosen
Provenance (4 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_69d886d6ba8c819093215917b3d01689 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42daab57c819093496cbdc7890f34 |
completed | April 19, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69e383141ae0819096acd71683637cbc |
completed | April 18, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69e39c2fedb881908bfed2c3e5f2616a |
completed | April 18, 2026, 2:58 p.m. |
Created at: April 10, 2026, 5:38 a.m.