Triple
T34949497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanpa |
E1007948
|
entity |
| Predicate | hasLayoutPlan |
P47409
|
FINISHED |
| Object | Kanpa Layout Plan No.1 |
—
|
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: Kanpa Layout Plan No.1 | Statement: [Kanpa, hasLayoutPlan, Kanpa Layout Plan No.1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLayoutPlan Context triple: [Kanpa, hasLayoutPlan, Kanpa Layout Plan No.1]
-
A.
hasPlan
Indicates that an entity possesses or is associated with a specific plan or course of action.
-
B.
hasPlanningLevel
Indicates that an entity is associated with a specific stage, tier, or granularity within a planning or scheduling hierarchy.
-
C.
hasLayout
Indicates that one entity defines or is associated with the structural arrangement or organization (layout) of another entity.
-
D.
hasStreetPlan
chosen
Indicates that an entity possesses or is associated with a specific layout or design plan for its streets.
-
E.
hasCampLayout
Indicates that an entity is associated with, or defined by, a specific arrangement or structural layout of a camp.
- 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_69f76dc5d4308190b77553ee07b1ede6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff64b957bc81908afbc5914234a8ea |
completed | May 9, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69ff6446593c81909173e296eea2590c |
completed | May 9, 2026, 4:43 p.m. |
Created at: May 3, 2026, 4 p.m.