Triple
T1847549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iowa City Downtown District |
E41317
|
entity |
| Predicate | hasPrimaryModeOfAccess |
P6865
|
FINISHED |
| Object | pedestrian 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: pedestrian traffic | Statement: [Iowa City Downtown District, hasPrimaryModeOfAccess, pedestrian traffic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryModeOfAccess Context triple: [Iowa City Downtown District, hasPrimaryModeOfAccess, pedestrian traffic]
-
A.
hasAccessMode
chosen
Indicates the type or method of access that one entity is permitted to use with respect to another entity or resource.
-
B.
hasPin
Indicates that one entity possesses, includes, or is equipped with a specific pin (such as a connector pin, security PIN, or fastening pin).
-
C.
hasFingerprintSensor
Indicates that an entity is equipped with or includes a fingerprint recognition sensor.
-
D.
hasPrimaryVehicularAccessTo
Indicates that one location or entity serves as the main route or means by which vehicles can reach or enter another location or entity.
-
E.
hasAccessModel
Indicates that one entity is permitted to use, interact with, or retrieve a particular model controlled by another entity or system.
- 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_69a88648cd44819093303206d96d76ad |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb32d35508190bf1c487dffbecaf0 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafdca6d8819083c66f3a29fd9fd1 |
completed | March 7, 2026, 4:55 a.m. |
Created at: March 4, 2026, 7:33 p.m.