Triple
T1306087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Market Street retail area |
E27880
|
entity |
| Predicate | hasFootfallPattern |
P27772
|
FINISHED |
| Object | peak at weekends |
—
|
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: peak at weekends | Statement: [Market Street retail area, hasFootfallPattern, peak at weekends]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFootfallPattern Context triple: [Market Street retail area, hasFootfallPattern, peak at weekends]
-
A.
hasSeasonalPattern
Indicates that the occurrence, intensity, or characteristics of something regularly vary according to a recurring seasonal cycle.
-
B.
hasCommuterPattern
Indicates that there is a characteristic or recurring pattern in how an entity regularly travels between locations, typically for work or daily activities.
-
C.
hasSettlementAtFoot
Indicates that a settlement is located at the base or lower slopes of a geographic feature such as a hill or mountain.
-
D.
locationPattern
Indicates a recurring or structured spatial relationship, where an entity consistently appears or is arranged in a particular type of location or spatial configuration.
-
E.
frequentlyVisitedBy
Indicates that an entity is regularly or often visited by another entity.
- F. None of above. chosen
Provenance (4 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_69a496d7d83481908f83085854e51328 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c15490a88190872c3d2698a8f9c9 |
completed | March 1, 2026, 10:44 p.m. |
| PD | Predicate disambiguation | batch_69a4bee9e4a88190b22ab2ee831a23c9 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c15361c8819094b8171e780b5560 |
completed | March 1, 2026, 10:44 p.m. |
Created at: March 1, 2026, 7:51 p.m.