Triple
T38342808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Street (Charleston) |
E1041452
|
entity |
| Predicate | isPedestrianDestination |
P190443
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [King Street (Charleston), isPedestrianDestination, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPedestrianDestination Context triple: [King Street (Charleston), isPedestrianDestination, true]
-
A.
isPedestrianNode
Indicates that the referenced node functions as a pedestrian-specific point in a network, such as a walkway, crossing, or footpath connection.
-
B.
isPedestrianFocus
Indicates that the primary attention or design consideration is directed toward pedestrians in a given context or environment.
-
C.
isPedestrianGateway
Indicates that something serves as an access point or entrance specifically intended for use by pedestrians.
-
D.
hasPedestrianAccessTo
Indicates that a location or area can be reached or entered safely and directly by people on foot.
-
E.
hasPedestrianFunction
Indicates that an entity serves a role, purpose, or function specifically related to pedestrians or pedestrian use.
- 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_69f76e2ad95481908c920c0e5c1c3e26 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fcc7a4d7f881908b43b960911b81e9 |
completed | May 7, 2026, 5:11 p.m. |
| PD | Predicate disambiguation | batch_69fcc589720c819089c8f500fea3c86a |
completed | May 7, 2026, 5:02 p.m. |
| PDg | Predicate description generation | batch_69fcc7a42f68819081d6ec8bb6b53438 |
completed | May 7, 2026, 5:11 p.m. |
Created at: May 3, 2026, 4:30 p.m.