Triple
T28272567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shangxiajiu Pedestrian Street |
E712895
|
entity |
| Predicate | hasTypicalVisitorActivity |
P157393
|
FINISHED |
| Object | shopping for clothes |
—
|
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: shopping for clothes | Statement: [Shangxiajiu Pedestrian Street, hasTypicalVisitorActivity, shopping for clothes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalVisitorActivity Context triple: [Shangxiajiu Pedestrian Street, hasTypicalVisitorActivity, shopping for clothes]
-
A.
hasVisitorActivities
chosen
Indicates that a place or entity offers or is associated with specific activities available for visitors to engage in.
-
B.
hasTypeOfVisitorExperience
Indicates that an entity is associated with a particular category or kind of visitor experience it provides or involves.
-
C.
hasHumanActivities
Indicates that certain human actions, behaviors, or practices are present, performed, or associated with a given entity.
-
D.
hasTouristVisits
Indicates that one entity experiences or records visits from tourists to another entity.
-
E.
hasVisitation
Indicates that one entity visits, or is allowed or scheduled to visit, another entity 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_69efb5216c6881908020dce4aea65381 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69fcef654d588190b29ecc76678d1aa0 |
completed | May 7, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69fcecdb97f48190b382b7d13be92dc0 |
completed | May 7, 2026, 7:49 p.m. |
Created at: April 27, 2026, 11:18 p.m.