Triple
T15464718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canton First Monday Flea Market |
E372000
|
entity |
| Predicate | hasApproximateDurationPerEvent |
P4874
|
FINISHED |
| Object | several days per month |
—
|
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: several days per month | Statement: [Canton First Monday Flea Market, hasApproximateDurationPerEvent, several days per month]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateDurationPerEvent Context triple: [Canton First Monday Flea Market, hasApproximateDurationPerEvent, several days per month]
-
A.
hasApproximateDuration
chosen
Indicates that one entity has a duration that is estimated or not exact, typically expressed as an approximate length of time.
-
B.
hasApproximateRate
Indicates that one entity is associated with another entity representing an estimated or non-exact rate or frequency.
-
C.
hasEventFrequency
Indicates how often a particular event occurs within a given time period.
-
D.
timePeriodApproximation
Indicates that the associated time period is an estimate or approximation rather than an exact, precise value.
-
E.
hasApproximateNumberOfRuns
Indicates that an entity is associated with a number of runs that is approximate rather than exact.
- 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_69d85cc8bd308190886949510b42e764 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f680cec8190836a5ec841dee224 |
completed | April 16, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69ded284bd008190b31c53b4f1cebadd |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:33 a.m.