Triple
T12349065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lanikai neighborhood |
E294435
|
entity |
| Predicate | hasAccessIssue |
P12603
|
FINISHED |
| Object | limited public parking |
—
|
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: limited public parking | Statement: [Lanikai neighborhood, hasAccessIssue, limited public parking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAccessIssue Context triple: [Lanikai neighborhood, hasAccessIssue, limited public parking]
-
A.
hasHumanAccess
Indicates that a human is able to access, use, or interact with the referenced entity or resource.
-
B.
hasDisabledAccess
Indicates that an entity provides facilities, features, or accommodations that make it accessible to people with disabilities.
-
C.
hadKeyIssue
Indicates that an entity experienced a primary or critical problem related to a key aspect, factor, or component.
-
D.
hasKeyIssue
chosen
Indicates that an entity is associated with a primary or central problem, concern, or topic of importance.
-
E.
hasAccessTo
Indicates that one entity is permitted to enter, use, or interact with another entity, resource, or location.
- 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f7ba17481908b03af7316b28d9b |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ecb5efc819086a3530282278bb1 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:53 p.m.