Triple
T26601714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Compagnie du Nord |
E667652
|
entity |
| Predicate | tradingFocus |
P67985
|
FINISHED |
| Object | Hudson Bay watershed |
—
|
NE NERFINISHED |
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: Hudson Bay watershed | Statement: [French Compagnie du Nord, tradingFocus, Hudson Bay watershed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tradingFocus Context triple: [French Compagnie du Nord, tradingFocus, Hudson Bay watershed]
-
A.
tradeFocus
chosen
Indicates a primary emphasis on or specialization in a particular type of trade, transaction, or commercial activity within the relationship or context.
-
B.
tradingApproach
Indicates the method or strategy an entity uses to conduct trading activities or make trade-related decisions.
-
C.
trades
Indicates an exchange relationship where one party gives something of value to another in return for something else of value.
-
D.
typeOfTrading
Indicates a relationship where one entity specifies the kind or category of trading activity associated with another entity.
-
E.
tradingSegment
Indicates that one entity operates within, or is associated with, a specific trading segment or market subdivision for transactional activities.
- 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_69ee9cfd20348190bb1255d2603efb7a |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f7465687bc8190a9da44d62b634ed7 |
completed | May 3, 2026, 12:57 p.m. |
| PD | Predicate disambiguation | batch_69f743f4ceb08190a21fe7f4a99b166b |
completed | May 3, 2026, 12:47 p.m. |
Created at: April 27, 2026, 2:12 a.m.