Triple
T11190345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christopher Columbus Monument |
E264779
|
entity |
| Predicate | subjectDepicts |
P49267
|
FINISHED |
| Object | Christopher Columbus pointing seaward |
—
|
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: Christopher Columbus pointing seaward | Statement: [Christopher Columbus Monument, subjectDepicts, Christopher Columbus pointing seaward]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectDepicts Context triple: [Christopher Columbus Monument, subjectDepicts, Christopher Columbus pointing seaward]
-
A.
typicallyDepicts
Indicates that one entity is most commonly or characteristically portrayed or represented by the other in depictions or images.
-
B.
depictedSubject
chosen
Indicates that one entity visually represents or portrays another entity as its subject in an image or depiction.
-
C.
imageDepictedIn
Indicates that a particular image is shown, represented, or included within another resource or context.
-
D.
subjectOfDescription
Indicates that the subject is the main entity being described or characterized in a given context or statement.
-
E.
depictsMood
Indicates that one entity visually represents or conveys the emotional state or mood of another entity.
- 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_69d6aa9eb9248190b20211772621b4bc |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8af18e4819091811bca657c9cb0 |
completed | April 9, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69d75cf4461c8190af84060f7db83211 |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:29 p.m.