Triple
T7876635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sullivan Center |
E182871
|
entity |
| Predicate | hasCornerFeature |
P42380
|
FINISHED |
| Object | rounded corner at State and Madison |
—
|
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: rounded corner at State and Madison | Statement: [Sullivan Center, hasCornerFeature, rounded corner at State and Madison]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCornerFeature Context triple: [Sullivan Center, hasCornerFeature, rounded corner at State and Madison]
-
A.
hasCorner
chosen
Indicates that one entity possesses or includes a corner that is part of or associated with another entity.
-
B.
hasSlopeFeature
Indicates that an entity possesses or is characterized by a particular slope-related property or feature.
-
C.
hasFrontFeature
Indicates that an entity possesses a specific characteristic, component, or attribute located on its front side.
-
D.
locatedAtCornerOf
Indicates that one entity is positioned at or forms the corner where two or more boundaries, edges, or intersecting paths meet.
-
E.
hasBoundaryFeature
Indicates that a boundary (such as an edge, border, or limit) of one entity is characterized, marked, or defined by a specific feature or element.
- 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_69ca828a17248190b46defe758bc5ad3 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39aa7ca88190b88a18f6a8971e51 |
completed | March 31, 2026, 3:04 a.m. |
| PD | Predicate disambiguation | batch_69cae928e1b88190b0620f4c4f03bc7d |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:57 p.m.