Triple
T12125727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Action Comics #1 |
E288804
|
entity |
| Predicate | hasLetterer |
P36863
|
FINISHED |
| Object | uncredited |
—
|
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: uncredited | Statement: [Action Comics #1, hasLetterer, uncredited]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLetterer Context triple: [Action Comics #1, hasLetterer, uncredited]
-
A.
letterer
chosen
Indicates that one entity serves as the letterer of another, typically responsible for drawing or designing the lettering (such as text or captions) in that work.
-
B.
hasLetterBy
Indicates that an entity possesses or is associated with a letter authored or sent by another entity.
-
C.
hasLetter
Indicates that one entity contains, includes, or is associated with a specific letter or character.
-
D.
hasLettersFor
Indicates that one entity possesses or contains written correspondence intended for another entity.
-
E.
hasLetterDesignation
Indicates that an entity is assigned or associated with a specific letter-based designation or code.
- 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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91841615c819097f20a7447a1b8f4 |
completed | April 10, 2026, 3:33 p.m. |
| PD | Predicate disambiguation | batch_69d91508f8008190b3a90ec0bf0953ca |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:49 p.m.