Triple
T12005317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aftermath |
E285764
|
entity |
| Predicate | longestTrackLength |
P23293
|
FINISHED |
| Object | over 11 minutes |
—
|
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: over 11 minutes | Statement: [Aftermath, longestTrackLength, over 11 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: longestTrackLength Context triple: [Aftermath, longestTrackLength, over 11 minutes]
-
A.
longestDurationAt
Indicates that one entity has the greatest length of time associated with a particular state, event, or activity compared to other relevant entities.
-
B.
maximumRecordedLength
chosen
Indicates the greatest length value that has been observed and recorded for the entity in question.
-
C.
lengthInMinutes
Indicates the duration of something expressed as a number of minutes.
-
D.
typicalTrackLengthRange
Indicates the usual minimum and maximum lengths that a track associated with something tends to fall between.
-
E.
lengthInSeconds
Indicates that one entity specifies the duration of another entity measured in seconds.
- 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_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903c481a48190b311d6809808ef1b |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d902b245cc8190af96a9c2bd9c6250 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.