Triple
T22851962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shisa figurines |
E566375
|
entity |
| Predicate | typicalArrangement |
P46737
|
FINISHED |
| Object | pair of statues |
—
|
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: pair of statues | Statement: [Shisa figurines, typicalArrangement, pair of statues]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalArrangement Context triple: [Shisa figurines, typicalArrangement, pair of statues]
-
A.
arrangementType
chosen
Indicates the specific kind or category of arrangement that characterizes how the related entities are organized or structured in relation to each other.
-
B.
commonlyArrangedFor
Indicates that one entity is typically organized, scheduled, or set up on behalf of another entity.
-
C.
arrangement
Indicates a relationship where entities are organized, ordered, or positioned in a particular configuration or sequence relative to one another.
-
D.
arranges
Indicates that one entity organizes, coordinates, or puts in order some event, objects, or circumstances involving another entity.
-
E.
isArrangementOf
Indicates that one entity is a specific ordering or configuration of the components or elements 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_69e2458750b481908a8e4cf4609cc6cf |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17eb9a5b8819091cbb4ac42fbf778 |
completed | April 29, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69eed2d507c08190895ed971af0fc755 |
completed | April 27, 2026, 3:07 a.m. |
Created at: April 17, 2026, 3:36 p.m.