Triple
T18438059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stall Street |
E450445
|
entity |
| Predicate | hasTouristFootfall |
P80470
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Stall Street, hasTouristFootfall, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTouristFootfall Context triple: [Stall Street, hasTouristFootfall, high]
-
A.
hasTouristVisits
Indicates that one entity experiences or records visits from tourists to another entity.
-
B.
hasTouristPopularity
Indicates that a place or attraction is recognized as being popular or frequently visited by tourists.
-
C.
hasFootfallPattern
Indicates a characteristic pattern or sequence of steps, movements, or impacts made by an entity’s feet during locomotion or activity.
-
D.
touristTraffic
chosen
Indicates the level, flow, or intensity of tourists visiting or moving through a particular place or area.
-
E.
shareTourismFlows
Indicates that two places are connected by or exchange significant tourism flows, such as visitors or tourist traffic, between them.
- 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_69d8d381d6388190a9e94e9c658174e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e51c0ed6708190ae90efd8455ec352 |
completed | April 19, 2026, 6:16 p.m. |
| PD | Predicate disambiguation | batch_69e469c943a4819094c8fdc5971ad3a7 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:29 a.m.