Triple
T20762270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Risk |
E511001
|
entity |
| Predicate | boardRepresents |
P39361
|
FINISHED |
| Object | world map |
—
|
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: world map | Statement: [Risk, boardRepresents, world map]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: boardRepresents Context triple: [Risk, boardRepresents, world map]
-
A.
board
Indicates that an agent gets onto or into a vehicle, vessel, or craft in order to travel or be transported.
-
B.
boardProperties
Indicates a relationship where specific attributes or characteristics are assigned to or associated with a board.
-
C.
cornerRepresents
Indicates that a particular corner in a structure, diagram, or space stands for or symbolizes another element, concept, or feature.
-
D.
componentRepresents
chosen
Indicates that one component stands in for, symbolizes, or models another entity or concept within a system or context.
-
E.
boardName
Indicates the name or title assigned to a specific board within a system or context.
- 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_69e0b4c909ec8190b05987f1639513f6 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2493a188190a336a35ea134e5f7 |
completed | April 21, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69e5c0509608819080cdbf47fcddfe36 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:35 p.m.