Triple
T24599881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buy More |
E608791
|
entity |
| Predicate | hasRecurringSettingElement |
P153979
|
FINISHED |
| Object | store sales floor |
—
|
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: store sales floor | Statement: [Buy More, hasRecurringSettingElement, store sales floor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecurringSettingElement Context triple: [Buy More, hasRecurringSettingElement, store sales floor]
-
A.
hasRecurringElement
Indicates that an entity includes an element that appears repeatedly or occurs multiple times within it.
-
B.
recurringSeriesSettingFor
chosen
Indicates that something serves as the setting or context in which a recurring series regularly takes place.
-
C.
hasRecurringRole
Indicates that an entity repeatedly appears or participates in a role within an ongoing or multiple related contexts over time.
-
D.
hasRecurringActor
Indicates that an actor appears repeatedly across multiple instances or episodes within a work or series.
-
E.
hasRecurringSetArea
Indicates that an entity is associated with an area or region that repeats or recurs according to a defined pattern or schedule.
- 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_69e2c4cf54248190af7b0c2d9ade9830 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:30 a.m.