Triple
T165455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Netflix, Inc. |
E3004
|
entity |
| Predicate | numberOfSubscribers |
P5639
|
FINISHED |
| Object | over 250 million global paid memberships (approximate, 2024) |
—
|
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 250 million global paid memberships (approximate, 2024) | Statement: [Netflix, Inc., numberOfSubscribers, over 250 million global paid memberships (approximate, 2024)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSubscribers Context triple: [Netflix, Inc., numberOfSubscribers, over 250 million global paid memberships (approximate, 2024)]
-
A.
numberOfParticipants
Indicates the total count of entities involved in a particular event, activity, or relationship.
-
B.
numberOfChildren
Indicates the total count of children that an entity has.
-
C.
numberOfBoardMembers
Indicates the total count of individuals who serve as members on a board.
-
D.
numberOfOrders
Indicates the total count of orders associated with a given entity or context.
-
E.
branchCount
Indicates the number of branches associated with a given entity or structure.
- 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_69a2524ce1e48190ab066bf72859f474 |
completed | Feb. 28, 2026, 2:26 a.m. |
| NER | Named-entity recognition | batch_69a25883ac8481909616b2179561bd98 |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a25664ba8081908ac298511a9fc5ba |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a256eb46ec81909c730000e5041d0d |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:34 a.m.