Triple
T38076323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Super Bowl V halftime show |
E950720
|
entity |
| Predicate | eventSequenceNumber |
P70742
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Super Bowl V halftime show, eventSequenceNumber, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eventSequenceNumber Context triple: [Super Bowl V halftime show, eventSequenceNumber, 5]
-
A.
sequenceInEvent
Indicates that one event occurs as a specific step or ordered part within a larger, encompassing event.
-
B.
programSequenceNumber
Indicates the position or order of a program within a sequence or series of programs.
-
C.
hasEventNumber
Indicates that an entity is associated with a specific event identified by a unique number.
-
D.
sequenceID
chosen
Indicates that an entity is associated with a specific position or identifier within an ordered sequence.
-
E.
engagementSequence
Indicates a temporal or logical ordering of engagement-related actions or interactions, showing how one engagement step follows or leads to another.
- 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_69f76f02a6c48190a94f3c0b3ee90cf2 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fc44c7e73c819082d4fc1900fb9632 |
completed | May 7, 2026, 7:52 a.m. |
| PD | Predicate disambiguation | batch_69fbc8efffbc8190a139798ad1880526 |
completed | May 6, 2026, 11:04 p.m. |
Created at: May 3, 2026, 4:21 p.m.