Triple
T24902011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madison Square |
E623603
|
entity |
| Predicate | streetBounding |
P108932
|
FINISHED |
| Object | East Charlton Street |
—
|
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: East Charlton Street | Statement: [Madison Square, streetBounding, East Charlton Street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: streetBounding Context triple: [Madison Square, streetBounding, East Charlton Street]
-
A.
hasRoadBoundary
Indicates that a road segment is associated with a specific boundary or edge that defines its lateral limits.
-
B.
fareBoundaryBetween
Indicates that there is a dividing line or zone where one fare region, zone, or pricing scheme ends and another begins.
-
C.
geographicBoundary
chosen
Indicates that one entity serves as a limiting border or edge that defines the geographic extent or separation of another entity.
-
D.
borderingLocalGovernmentArea
Indicates that one local government area shares a common boundary with another local government area.
-
E.
streetGridRange
Indicates the span or extent of a street segment within a defined grid or block range in a street network.
- 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_69e2fac797cc8190b30d77f4121099ac |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f47b865df48190bf4b6d3e9f9305e6 |
completed | May 1, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69f4682c8a3c8190adbfaac99474eaaf |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 18, 2026, 5:27 a.m.