Triple
T29435284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben Affleck as George Reeves |
E746553
|
entity |
| Predicate | depictsWorkOfCharacter |
P128744
|
FINISHED |
| Object | Adventures of Superman (TV series) |
—
|
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: Adventures of Superman (TV series) | Statement: [Ben Affleck as George Reeves, depictsWorkOfCharacter, Adventures of Superman (TV series)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsWorkOfCharacter Context triple: [Ben Affleck as George Reeves, depictsWorkOfCharacter, Adventures of Superman (TV series)]
-
A.
depictsAuthorOf
Indicates that one entity visually represents or portrays the person who is the author of another entity.
-
B.
depictsLiteraryWork
chosen
Indicates that one entity visually represents, illustrates, or portrays the content, scenes, or themes of a specific literary work.
-
C.
depictsCharacterType
Indicates that one entity visually represents or portrays a character of a specified type or role.
-
D.
literaryCharacterDepicted
Indicates that a literary character is visually or textually represented in a work such as an image, illustration, or other medium.
-
E.
depictionBasedOn
Indicates that one depiction is created using another work, image, or representation as its source or reference.
- 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_69f0a7a180e48190ae775e40047dbcb5 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f73ae120bc8190bff94d38d7a7a00d |
completed | May 3, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69f73a38d0848190aa5139144b8561c6 |
completed | May 3, 2026, 12:06 p.m. |
Created at: April 28, 2026, 3:16 p.m.