Triple
T1479835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | High Park |
E30925
|
entity |
| Predicate | typicalVisitorActivities |
P1164
|
FINISHED |
| Object | walking |
—
|
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: walking | Statement: [High Park, typicalVisitorActivities, walking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalVisitorActivities Context triple: [High Park, typicalVisitorActivities, walking]
-
A.
typicalActivity
chosen
Indicates that an entity is commonly or characteristically engaged in a particular activity.
-
B.
isMajorAttractionFor
Indicates that something serves as a primary or highly significant draw or point of interest for a particular audience, group, or location.
-
C.
activityType
Indicates the specific kind or category of action or event that an entity is engaged in or associated with.
-
D.
hasRecreationActivity
Indicates that an entity provides, includes, or is associated with a particular recreational activity.
-
E.
offersDayPlacesTo
Indicates that one entity provides or makes available daytime places or slots to another entity.
- 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_69a498fe55a88190ab7f9e40ace88e49 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c674cc9c819088fc9146c7a7a914 |
completed | March 1, 2026, 11:06 p.m. |
| PD | Predicate disambiguation | batch_69a4c484e52c81908948ff8c0a42751b |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:11 p.m.