Triple
T25147822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Wilson Carmichael |
E629983
|
entity |
| Predicate | depictedTopic |
P123416
|
FINISHED |
| Object | merchant shipping |
—
|
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: merchant shipping | Statement: [John Wilson Carmichael, depictedTopic, merchant shipping]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictedTopic Context triple: [John Wilson Carmichael, depictedTopic, merchant shipping]
-
A.
depictedSubject
Indicates that one entity visually represents or portrays another entity as its subject in an image or depiction.
-
B.
typicallyDepicts
Indicates that one entity is most commonly or characteristically portrayed or represented by the other in depictions or images.
-
C.
fieldOfDepiction
chosen
Indicates that one entity serves as the subject matter or thematic focus depicted within another entity, such as an image, artwork, or representation.
-
D.
topicOfDialogue
Indicates that a particular subject or theme is the main focus of a dialogue or conversation between entities.
-
E.
notableForDepicting
Indicates that something is recognized or distinguished specifically for portraying or representing a particular subject, theme, or scene.
- 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_69e2ff349e408190a6f4a5a66279f54d |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f497bc12b881908fe3386c66252bf6 |
completed | May 1, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69f49366e8d08190adb4b71fe3a14683 |
completed | May 1, 2026, 11:49 a.m. |
Created at: April 18, 2026, 6:30 a.m.