Triple
T1516877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trinity Street, Cambridge |
E32140
|
entity |
| Predicate | pedestrianActivity |
P29968
|
FINISHED |
| Object | heavy foot traffic |
—
|
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: heavy foot traffic | Statement: [Trinity Street, Cambridge, pedestrianActivity, heavy foot traffic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pedestrianActivity Context triple: [Trinity Street, Cambridge, pedestrianActivity, heavy foot traffic]
-
A.
pedestrianFriendly
Indicates that an environment, route, or area is designed or suitable for safe, comfortable, and convenient use by pedestrians.
-
B.
pedestrianOnly
Indicates that a path, area, or route is designated exclusively for pedestrians and prohibits vehicle access.
-
C.
pedestrianRestrictions
Indicates that there are specific rules or limitations governing where or how pedestrians may travel or access an area.
-
D.
hasPedestrianAccessTo
Indicates that a location or area can be reached or entered safely and directly by people on foot.
-
E.
hasPedestrianArea
Indicates that a location or zone includes a designated area intended for pedestrian use only or primarily.
- F. None of above. chosen
Provenance (4 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_69a885e8caf88190a5fbb6159ce87786 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9396e16408190b5e7b0ac43376d81 |
completed | March 5, 2026, 8:06 a.m. |
| PD | Predicate disambiguation | batch_69a907aa67cc81909f00135365447399 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69a9396d3e1081909aa269b42041c357 |
completed | March 5, 2026, 8:06 a.m. |
Created at: March 4, 2026, 7:26 p.m.