Triple
T2480999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old City, Philadelphia |
E55813
|
entity |
| Predicate | streetGridFeatures |
P1777
|
FINISHED |
| Object | cobblestone 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: cobblestone streets | Statement: [Old City, Philadelphia, streetGridFeatures, cobblestone streets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: streetGridFeatures Context triple: [Old City, Philadelphia, streetGridFeatures, cobblestone streets]
-
A.
streetGridOrientation
Indicates the predominant directional alignment or pattern of streets within a given area or city layout.
-
B.
hasStreetGridPattern
Indicates that an area’s street layout follows a structured, grid-like pattern of intersecting roads.
-
C.
streetNetwork
Indicates the layout and connectivity relationships among streets within a geographic area, including how roads intersect, link, and form a navigable network.
-
D.
roadFeature
chosen
Indicates that an entity is a specific physical or functional characteristic associated with a road, such as its structure, markings, or related infrastructure.
-
E.
streetLocation
Indicates that one entity is located on, along, or at a specific street associated with the other entity.
- 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_69ab49e670a88190b928e08302381710 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd20b6d008190acec0eb172e218c9 |
completed | March 7, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69abd0b7cf088190bcff4dac6150044c |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:45 p.m.