Triple
T26515221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adam Meiks |
E669794
|
entity |
| Predicate | hasAdultVersionPortrayedBy |
P103333
|
FINISHED |
| Object | Matthew McConaughey |
—
|
NE NERFINISHED |
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: Matthew McConaughey | Statement: [Adam Meiks, hasAdultVersionPortrayedBy, Matthew McConaughey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdultVersionPortrayedBy Context triple: [Adam Meiks, hasAdultVersionPortrayedBy, Matthew McConaughey]
-
A.
portrayedAsAdultBy
chosen
Indicates that one entity is depicted or represented as an adult by another entity (such as an artist, author, or creator).
-
B.
appearsAsAdultIn
Indicates that an entity is depicted or presented in its adult form within a specified context, such as a work, scene, or time period.
-
C.
hasAdultRank
Indicates that an entity holds a status or position classified as an adult-level rank within a given system or hierarchy.
-
D.
isAdultCharacter
Indicates that a character has reached adulthood, typically meeting the age or maturity criteria defining an adult within the given context.
-
E.
containsAdultContent
Indicates that the referenced item includes material intended for adults, such as explicit sexual, violent, or otherwise age-restricted content.
- 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_69eeb31b6dcc8190b30632dc3928a0c0 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f67f0488bc819089fbd2d2478158d3 |
completed | May 2, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69f67e3ed894819094c067c1ef624951 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 27, 2026, 1:23 a.m.