Triple
T109323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AOL |
E2208
|
entity |
| Predicate | peakSubscriberCount |
P4549
|
FINISHED |
| Object | over 30 million subscribers |
—
|
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 30 million subscribers | Statement: [AOL, peakSubscriberCount, over 30 million subscribers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peakSubscriberCount Context triple: [AOL, peakSubscriberCount, over 30 million subscribers]
-
A.
peakPopularity
Indicates the time or context in which something reaches its highest level of popularity relative to other times or contexts.
-
B.
memberCountAtPeak
chosen
Indicates the highest number of members that an entity (such as a group or organization) has had at any point in time.
-
C.
visitorCount
Indicates the number of visitors associated with a particular entity, context, or time period.
-
D.
approximateAudienceSize
Indicates an estimated number of individuals or entities that are expected to be reached or affected in a given context.
-
E.
popularInPeriod
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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a25711f6788190a22252ea3a3af394 |
completed | Feb. 28, 2026, 2:46 a.m. |
| PD | Predicate disambiguation | batch_69a2563fd2fc819090265edbfe3092d6 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.