Triple
T12560708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bloomfield (Pittsburgh) |
E295332
|
entity |
| Predicate | hasStreetGridCharacteristic |
P82324
|
FINISHED |
| Object | narrow 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: narrow streets | Statement: [Bloomfield (Pittsburgh), hasStreetGridCharacteristic, narrow streets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStreetGridCharacteristic Context triple: [Bloomfield (Pittsburgh), hasStreetGridCharacteristic, narrow streets]
-
A.
hasStreetGridFeature
chosen
Indicates that a location or area possesses a specific characteristic or element of a street grid layout, such as a particular pattern, structure, or feature of its road network.
-
B.
hasStreetGridPattern
Indicates that an area’s street layout follows a structured, grid-like pattern of intersecting roads.
-
C.
streetGridOrientation
Indicates the predominant directional alignment or pattern of streets within a given area or city layout.
-
D.
hasNumberOfStreets
Indicates the relationship that specifies how many streets are associated with or contained within a given entity.
-
E.
hasTreeLinedStreets
Indicates that the streets in a given area are lined or bordered with trees along their sides.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9550d84908190aea0f50055f6d92e |
completed | April 10, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69d95414692881909c52a1de7d224b44 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 11:48 p.m.