Triple
T18111768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aimee Marcos |
E433493
|
entity |
| Predicate | mediaExposureLevel |
P37618
|
FINISHED |
| Object | lower than other Marcos siblings |
—
|
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: lower than other Marcos siblings | Statement: [Aimee Marcos, mediaExposureLevel, lower than other Marcos siblings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mediaExposureLevel Context triple: [Aimee Marcos, mediaExposureLevel, lower than other Marcos siblings]
-
A.
mediaExposure
chosen
Indicates the extent to which an entity is subjected to or receives attention from media channels such as television, radio, print, or online platforms.
-
B.
mediaConsumption
Indicates the act or pattern of engaging with, using, or experiencing media content (such as watching, listening, or reading).
-
C.
televisionExposureLevel
Indicates the degree or amount of exposure an entity has to television content.
-
D.
exposureLevel
Indicates the degree or intensity to which an entity is subjected or exposed to a particular factor, condition, or influence.
-
E.
mediaFocus
Indicates that the primary attention, coverage, or emphasis of a media source is directed toward a particular entity or topic.
- 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddd3422c81908396a21bd53f3e47 |
completed | April 19, 2026, 1:51 p.m. |
| PD | Predicate disambiguation | batch_69e43313ca788190baa224269e71de49 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:28 a.m.