Triple
T1973765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stockton Street |
E42858
|
entity |
| Predicate | hasPedestrianActivityLevel |
P19607
|
FINISHED |
| Object | very high |
—
|
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: very high | Statement: [Stockton Street, hasPedestrianActivityLevel, very high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPedestrianActivityLevel Context triple: [Stockton Street, hasPedestrianActivityLevel, very high]
-
A.
hasPedestrianTrafficLevel
chosen
Indicates the level or intensity of pedestrian traffic associated with a given location or pathway.
-
B.
pedestrianActivity
Indicates that an entity is engaged in or associated with walking or other on-foot movement or behavior.
-
C.
hasPedestrianArea
Indicates that a location or zone includes a designated area intended for pedestrian use only or primarily.
-
D.
hasPedestrianAccessTo
Indicates that a location or area can be reached or entered safely and directly by people on foot.
-
E.
hasPedestrianCharacter
Indicates that something possesses qualities, features, or behavior characteristic of pedestrians or pedestrian use.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb3f477988190b0165fc46b1cccfd |
completed | March 7, 2026, 5:13 a.m. |
| PD | Predicate disambiguation | batch_69abaff7d4a48190ab0d51aefb1c4e31 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.