Triple
T35316896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Foster |
E1019927
|
entity |
| Predicate | hasWriterDepictions |
P182727
|
FINISHED |
| Object | various Marvel writers |
—
|
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: various Marvel writers | Statement: [Tom Foster, hasWriterDepictions, various Marvel writers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWriterDepictions Context triple: [Tom Foster, hasWriterDepictions, various Marvel writers]
-
A.
depictsAuthorOf
Indicates that one entity visually represents or portrays the person who is the author of another entity.
-
B.
screenwriterDepictionBy
Indicates a relationship where a screenwriter is portrayed or represented by another entity, such as in a work, record, or description.
-
C.
depictedInAuthor
Indicates that an author is visually represented or portrayed within a particular work or depiction.
-
D.
hasAllegoricalDepictionsBy
Indicates that one entity is represented through allegorical depictions created by another entity.
-
E.
hasNotableIllustrationsOf
Indicates that something contains or features particularly significant or noteworthy illustrations depicting another entity or subject.
- F. None of above. chosen
Provenance (4 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_69f76de9d45c81908a2ed0956b448b65 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f790929a888190aa7084a792c304fc |
completed | May 3, 2026, 6:14 p.m. |
| PD | Predicate disambiguation | batch_69f78e2f52e08190a77661223a96c601 |
completed | May 3, 2026, 6:04 p.m. |
| PDg | Predicate description generation | batch_69f78f629d508190b755848162c4e101 |
completed | May 3, 2026, 6:09 p.m. |
Created at: May 3, 2026, 4:03 p.m.