Triple
T2604248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EFL League One |
E58618
|
entity |
| Predicate | typicalMatchDays |
P34404
|
FINISHED |
| Object | 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: weekends | Statement: [EFL League One, typicalMatchDays, weekends]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalMatchDays Context triple: [EFL League One, typicalMatchDays, weekends]
-
A.
typicalMatchType
Indicates the usual or most common type of match or pairing that characterizes how two entities are related or aligned.
-
B.
typicalNumberOfMeetingsPerSeason
Indicates the usual or average count of meetings that occur within a single season.
-
C.
matchupFrequency
Indicates how often a particular pair or set of entities are matched or paired against each other within a given context or timeframe.
-
D.
typicalEventDay
chosen
Indicates the day on which an event is normally or most commonly held or occurs.
-
E.
typicalDates
Indicates the usual or standard dates during which something typically occurs, is valid, or is scheduled.
- 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_69ab4ac3523881909679750c9f8c2dec |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8def9bc8190b2e013abffc7b191 |
completed | March 7, 2026, 7:50 a.m. |
| PD | Predicate disambiguation | batch_69abd80ab7248190ba06ba14fe4c5638 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:49 p.m.