Triple
T31504881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Super Viernes |
E803789
|
entity |
| Predicate | typicalAttendanceType |
P65012
|
FINISHED |
| Object | live audience |
—
|
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: live audience | Statement: [Super Viernes, typicalAttendanceType, live audience]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAttendanceType Context triple: [Super Viernes, typicalAttendanceType, live audience]
-
A.
hasTypicalAttendance
Indicates the usual or characteristic number of attendees associated with an event, venue, or activity.
-
B.
hasAttendanceType
chosen
Indicates the specific category or mode of attendance associated with an event or participant (e.g., in-person, virtual, hybrid).
-
C.
attendanceCategory
Indicates the classification or type assigned to an entity’s attendance status within a given context or event.
-
D.
typicalVisitType
Indicates the usual or most common category of visit associated with an entity or event.
-
E.
attendanceRecordMatchType
Indicates how closely or in what manner an attendance record corresponds or matches to a given reference or expected record.
- 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_69f348cae52081909fa8e5f697523ae3 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e7aa0c8190bdc9ee4d54fc821b |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 30, 2026, 9:46 p.m.