Triple
T3338839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cambridge Street (Boston) |
E70208
|
entity |
| Predicate | hasNeighborhoodFunction |
P28961
|
FINISHED |
| Object | commercial corridor |
—
|
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: commercial corridor | Statement: [Cambridge Street (Boston), hasNeighborhoodFunction, commercial corridor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNeighborhoodFunction Context triple: [Cambridge Street (Boston), hasNeighborhoodFunction, commercial corridor]
-
A.
hasNeighborhoodAlong
Indicates that one entity has a neighboring area or region that extends along the boundary or length of another entity.
-
B.
hasNearbyFunction
chosen
Indicates that one entity has another entity located close by that serves a related or supportive function.
-
C.
hasNeighbourhood
Indicates that one entity is located within, or is associated with, a particular neighborhood area of another entity.
-
D.
hasNeighborhoodAssociation
Indicates that an entity is associated with, or falls under the jurisdiction of, a particular neighborhood association.
-
E.
runsThroughNeighborhood
Indicates that something (such as a route, path, or service) passes through or traverses a particular neighborhood.
- 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_69ad85a405e48190b6e68de7cf9f319e |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb1bd6c7c8190b7229de1433d8d20 |
completed | March 8, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69ada42c2ba8819091136805ce17b39d |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:12 p.m.