Triple
T36491746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Omniglot |
E899066
|
entity |
| Predicate | eachClassDrawnBy |
P185600
|
FINISHED |
| Object | multiple different people |
—
|
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: multiple different people | Statement: [Omniglot, eachClassDrawnBy, multiple different people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eachClassDrawnBy Context triple: [Omniglot, eachClassDrawnBy, multiple different people]
-
A.
ifDrawn
Indicates that one entity is drawn or selected as a consequence or result of another specified condition or event.
-
B.
drawnTo
Indicates that one entity is attracted or pulled toward another entity, whether physically, emotionally, or conceptually.
-
C.
depictsClass
Indicates that one entity visually represents or portrays a particular class or category of entities.
-
D.
drawnUnder
Indicates that one entity is depicted or represented as being beneath another entity in a drawing or visual representation.
-
E.
drawsLesson
Indicates that one entity derives or infers a lesson or conclusion from another entity or situation.
- 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bccf05bc8190b61fdb2b2a315811 |
completed | May 3, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69f7be9b9ab481908328e0e8d8ac73d4 |
completed | May 3, 2026, 9:31 p.m. |
Created at: May 3, 2026, 4:10 p.m.