Triple
T28740614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Castro Street |
E731227
|
entity |
| Predicate | hasNearbyIntersectionWith |
P49266
|
FINISHED |
| Object | Market 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: Market Street | Statement: [Castro Street, hasNearbyIntersectionWith, Market Street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyIntersectionWith Context triple: [Castro Street, hasNearbyIntersectionWith, Market Street]
-
A.
hasNearbyPoint
Indicates that one entity has at least one other point located within a specified proximity or distance from it.
-
B.
hasNearbyCrossingPoint
chosen
Indicates that one location has a crossing point (such as a bridge, crosswalk, or intersection) situated close to it.
-
C.
hasNeighboringObject
Indicates that one object is located adjacent to or directly next to another object in space.
-
D.
hasNearbyBoundary
Indicates that one entity’s boundary lies close to, but does not necessarily touch or coincide with, the boundary of another entity.
-
E.
hasNotableIntersection
Indicates that two entities intersect or cross at a point that is considered significant or noteworthy in some context.
- 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_69f043ecb5c081909ec9da1172d68ece |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69fda5003cdc8190a558501271389912 |
completed | May 8, 2026, 8:55 a.m. |
| PD | Predicate disambiguation | batch_69fda05bfc2c819096821a5300e9bb24 |
completed | May 8, 2026, 8:35 a.m. |
Created at: April 28, 2026, 6:02 a.m.