Triple
T29994658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Force Computers |
E761985
|
entity |
| Predicate | notableRegionOfOperation |
P200211
|
FINISHED |
| Object | North America |
E335
|
NE 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: North America | Statement: [Force Computers, notableRegionOfOperation, North America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableRegionOfOperation Context triple: [Force Computers, notableRegionOfOperation, North America]
-
A.
notableOperationArea
Indicates the geographic area or region where an entity primarily conducts or is recognized for its significant operations or activities.
-
B.
regionOfPrimaryOperation
chosen
Indicates the geographic area where an entity primarily conducts its main activities or operations.
-
C.
notableRegionOfBusiness
Indicates that a specified geographic region is a significant or primary area in which an entity conducts its business activities.
-
D.
operatedInRegion
Indicates that an entity conducted operations or activities within a specified geographic region.
-
E.
hasNotableUsageRegion
Indicates that something is prominently or distinctively used within a particular geographic region.
- F. None of above.
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_69f224695498819094a81037cad401e2 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2721f00e548190b5afd8461a555d9d |
completed | June 8, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_6a0379e0f3d88190a4ee7b0673f1ef90 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 6:39 p.m.