Triple
T185463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Syndics of the Drapers’ Guild |
E3969
|
entity |
| Predicate | depictsObject |
P1581
|
FINISHED |
| Object | sample book of cloth |
—
|
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: sample book of cloth | Statement: [The Syndics of the Drapers’ Guild, depictsObject, sample book of cloth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsObject Context triple: [The Syndics of the Drapers’ Guild, depictsObject, sample book of cloth]
-
A.
depicts
chosen
Indicates that one entity visually represents, portrays, or shows another entity.
-
B.
depictsPerson
Indicates that one entity visually represents or portrays a specific person.
-
C.
depictsInstitution
Indicates that one entity visually represents or portrays an institution as its subject.
-
D.
embodiedBy
Indicates that an abstract concept, role, or function is physically or concretely realized in a specific entity.
-
E.
describes
Indicates that one entity provides an explanation, representation, or account of another entity or concept.
- 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a2592867108190b5d316c055575449 |
completed | Feb. 28, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69a2566fb08c81908faff2fde552105d |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:40 a.m.