Triple
T4660659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zytglogge |
E102519
|
entity |
| Predicate | hasAnimatedFigures |
P58268
|
FINISHED |
| Object | rooster |
—
|
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: rooster | Statement: [Zytglogge, hasAnimatedFigures, rooster]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAnimatedFigures Context triple: [Zytglogge, hasAnimatedFigures, rooster]
-
A.
numberOfFiguresDepicted
Indicates the total count of distinct figures shown within a given depiction or representation.
-
B.
commonlyDepictedOn
Indicates that something is frequently shown or represented on the surface, medium, or context of another thing.
-
C.
hasIllustrations
Indicates that an entity includes or is accompanied by visual illustrations.
-
D.
hasIllustrationsBy
Indicates that one entity (such as a work or publication) includes illustrations that were created by another entity (the illustrator).
-
E.
hasFictionalForm
Indicates that an entity has a counterpart or representation that exists within a fictional or imaginary context.
- 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_69bd43d823288190952279faa0d1d066 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd632a17cc8190bcdab0a13b89f5c0 |
completed | March 20, 2026, 3:09 p.m. |
| PD | Predicate disambiguation | batch_69bd62126b0c81909ba3f21b21e30d54 |
completed | March 20, 2026, 3:04 p.m. |
| PDg | Predicate description generation | batch_69bd631328fc81909b28ae0a2a3ed9bb |
completed | March 20, 2026, 3:09 p.m. |
Created at: March 20, 2026, 1:15 p.m.