Triple
T17544356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Dad Is 100 Years Old |
E427285
|
entity |
| Predicate | portraysMultipleCharacters |
P32517
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [My Dad Is 100 Years Old, portraysMultipleCharacters, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysMultipleCharacters Context triple: [My Dad Is 100 Years Old, portraysMultipleCharacters, true]
-
A.
portrayedVia
Indicates that one entity is represented, depicted, or expressed through a particular medium, method, or channel.
-
B.
portraysCharacterInGenre
Indicates that an entity depicts or plays a character within works belonging to a specified genre.
-
C.
portraysMainCharacter
Indicates that one entity depicts or represents another entity as the primary or central character in a work or narrative.
-
D.
featuresActorInMultipleRoles
chosen
Indicates that a work includes an actor who portrays more than one distinct role within that same work.
-
E.
alsoPortrayedBy
Indicates that the same role or character is portrayed by an additional, different performer or actor.
- 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_69d889df6dc081908f67dbadc03c07ee |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e454609bdc8190b81b362906e7e3fd |
completed | April 19, 2026, 4:04 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fb39948190a82a597c5bac5c57 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:49 a.m.