Triple
T9138397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CMLL Anniversary Show |
E219261
|
entity |
| Predicate | hasTypicalAttendance |
P87333
|
FINISHED |
| Object | thousands of spectators |
—
|
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: thousands of spectators | Statement: [CMLL Anniversary Show, hasTypicalAttendance, thousands of spectators]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalAttendance Context triple: [CMLL Anniversary Show, hasTypicalAttendance, thousands of spectators]
-
A.
hasAttendanceType
Indicates the specific category or mode of attendance associated with an event or participant (e.g., in-person, virtual, hybrid).
-
B.
attendance
Indicates the relationship between an event and the people who are present at or participate in that event.
-
C.
attendanceAnnounced
Indicates that an official statement has been made about whether and/or how many people will attend an event.
-
D.
laterAttends
Indicates that one entity attends an event or place at a time later than another referenced attendance.
-
E.
isRegularAt
Indicates that a function or mapping behaves regularly (e.g., is analytic, smooth, or non-singular) at a specified point or region, without irregularities or singularities there.
- 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_69ca83e012288190a5771058adbaabd2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8efe3b88190a55a15827e6817a4 |
completed | April 1, 2026, 5:11 a.m. |
| PD | Predicate disambiguation | batch_69cc6601d77881908299d58db6e64937 |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc6a3c78388190a7436acc0e44ff55 |
completed | April 1, 2026, 12:43 a.m. |
Created at: March 30, 2026, 7:19 p.m.