Triple
T17420487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jefferson Park Golf Course |
E423598
|
entity |
| Predicate | isWalkingFriendly |
P13973
|
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: [Jefferson Park Golf Course, isWalkingFriendly, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isWalkingFriendly Context triple: [Jefferson Park Golf Course, isWalkingFriendly, true]
-
A.
hasWalkingPathAround
Indicates that one entity has a walking path that encircles or runs around another entity.
-
B.
hasWalkingRouteType
Indicates that an entity is associated with a specific type or category of walking route (e.g., trail, path, or walking itinerary).
-
C.
isWalkable
Indicates that an entity can be traversed on foot, typically without obstruction or restriction.
-
D.
isFriendOfProtagonist
Indicates that one entity is a friend or close ally of the story’s main character.
-
E.
pedestrianFriendly
chosen
Indicates that an environment, route, or area is designed or suitable for safe, comfortable, and convenient use by pedestrians.
- 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e442372954819085f332efc7067ae9 |
completed | April 19, 2026, 2:47 a.m. |
| PD | Predicate disambiguation | batch_69e3b02e6cc88190986e85e64ce9383e |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:46 a.m.