Triple
T3032106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IPTV |
E82918
|
entity |
| Predicate | becamePopularIn |
P3813
|
FINISHED |
| Object | 2000s |
—
|
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: 2000s | Statement: [IPTV, becamePopularIn, 2000s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: becamePopularIn Context triple: [IPTV, becamePopularIn, 2000s]
-
A.
popularizedIn
Indicates that something became widely known, accepted, or fashionable within a particular place, time period, or context.
-
B.
popularizedBy
Indicates that something became widely known, accepted, or fashionable as a result of the influence or actions of a particular agent.
-
C.
historicallyPopularIn
Indicates that something was notably popular or widely favored within a particular place or context during a past historical period.
-
D.
becameBreakoutHitFor
Indicates that something achieved sudden, widespread popularity or success specifically in relation to a particular entity (such as an artist, brand, or market).
-
E.
popularInPeriod
chosen
Indicates that something is widely liked, used, or influential during a specified time period.
- 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_69ad8b21a62881908ec5dd4fba4a187c |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9aefc2dc8190ad9b349ca45b7e30 |
completed | March 8, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69ad961e2a408190afb1759132701305 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:01 p.m.