Triple
T4172022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Instagram Reels |
E84584
|
entity |
| Predicate | supportsVideoLengthRange |
P54504
|
FINISHED |
| Object | 15–90 seconds |
—
|
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: 15–90 seconds | Statement: [Instagram Reels, supportsVideoLengthRange, 15–90 seconds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsVideoLengthRange Context triple: [Instagram Reels, supportsVideoLengthRange, 15–90 seconds]
-
A.
maximumVideoLength
Indicates the greatest allowable or supported duration for a video in this context.
-
B.
typicalRecordingDuration
Indicates the usual or standard length of time that something is recorded.
-
C.
hasEpisodeLengthType
Indicates the type or category of duration associated with an episode (e.g., standard length, short, extended).
-
D.
lengthInMinutes
Indicates the duration of something expressed as a number of minutes.
-
E.
maximumRecordedLength
Indicates the greatest length value that has been observed and recorded for the entity in question.
- 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_69aed932cab48190b80ffe35f7029ae1 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02c9e12c81908d0b22671fea2453 |
completed | March 9, 2026, 5:26 p.m. |
| PD | Predicate disambiguation | batch_69af018fb0948190a9701b2e8e5d9bac |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af01ee94ec8190aa6dde54d4571c04 |
completed | March 9, 2026, 5:22 p.m. |
Created at: March 9, 2026, 3:45 p.m.