Triple
T14551396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | equestrian statue of General Ulysses S. Grant (Brooklyn) |
E341425
|
entity |
| Predicate | hasDepictsRole |
P17608
|
FINISHED |
| Object | Union Army general |
—
|
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: Union Army general | Statement: [equestrian statue of General Ulysses S. Grant (Brooklyn), hasDepictsRole, Union Army general]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDepictsRole Context triple: [equestrian statue of General Ulysses S. Grant (Brooklyn), hasDepictsRole, Union Army general]
-
A.
depictsPersonRole
chosen
Indicates that an image or representation shows a person in a specific role, function, or capacity.
-
B.
playsInRole
Indicates that an entity performs or appears in a specific role within a production, event, or context.
-
C.
representedRole
Indicates that one entity serves as a stand-in, proxy, or representative performing a role on behalf of another entity.
-
D.
depictsAttribute
Indicates that one entity visually represents or illustrates a specific attribute or characteristic of another entity.
-
E.
depictsName
Indicates that something visually represents or portrays the name of an 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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb2ee34208190bf040a513767c958 |
completed | April 14, 2026, 9:34 p.m. |
| PD | Predicate disambiguation | batch_69de5c546c7081909e27d504ec360c5c |
completed | April 14, 2026, 3:25 p.m. |
Created at: April 10, 2026, 1:23 a.m.