Triple
T10554649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christine Diane Teigen |
E249043
|
entity |
| Predicate | hasTwitterFollowersOver |
P73542
|
FINISHED |
| Object | 10 million |
—
|
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: 10 million | Statement: [Christine Diane Teigen, hasTwitterFollowersOver, 10 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTwitterFollowersOver Context triple: [Christine Diane Teigen, hasTwitterFollowersOver, 10 million]
-
A.
hasFollowers
Indicates that an entity is followed or subscribed to by one or more other entities.
-
B.
followsApproximately
Indicates that one entity follows another in sequence or order, but with some allowable deviation or inexactness in timing, position, or pattern.
-
C.
hasMajorFollowingAmong
Indicates that the subject is widely popular or influential within the specified group or audience.
-
D.
followersCalled
Indicates that one entity refers to or addresses its followers by a specific name or term.
-
E.
socialMediaFollowerCount
chosen
Indicates the number of followers an entity has on a social media platform.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d527118da081909ca61bc555a17609 |
completed | April 7, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69d518fa0b4081909bffc936d78bd77b |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:34 p.m.