Triple
T4085271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Legends Outlets Kansas City |
E87573
|
entity |
| Predicate | hasWalkingAreas |
P18406
|
FINISHED |
| Object | pedestrian-friendly streets |
—
|
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-friendly streets | Statement: [Legends Outlets Kansas City, hasWalkingAreas, pedestrian-friendly streets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWalkingAreas Context triple: [Legends Outlets Kansas City, hasWalkingAreas, pedestrian-friendly streets]
-
A.
hasPedestrianArea
chosen
Indicates that a location or zone includes a designated area intended for pedestrian use only or primarily.
-
B.
hasStandingArea
Indicates that an entity includes or provides a designated area where people can stand.
-
C.
hasSafeStandingAreas
Indicates that designated locations within an area provide secure, stable, and protected spots where individuals can safely stand.
-
D.
isWalkable
Indicates that an entity can be traversed on foot, typically without obstruction or restriction.
-
E.
hasRecreationalArea
Indicates that an entity includes, provides, or is associated with a designated space intended for leisure or recreational activities.
- 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_69aed9435cf48190ad1da737c962d19d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc7b7cc4819089cfbf2b1c23ccc5 |
completed | March 9, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69aef909c9c88190b09d48dad325a83c |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:39 p.m.