Triple
T14321683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trading post |
E355103
|
entity |
| Predicate | typicalGoodsTraded |
P53553
|
FINISHED |
| Object | furs |
—
|
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: furs | Statement: [Trading post, typicalGoodsTraded, furs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalGoodsTraded Context triple: [Trading post, typicalGoodsTraded, furs]
-
A.
typicalGoodsSold
chosen
Indicates the kinds of goods or products that an entity most commonly or characteristically sells.
-
B.
majorTradeType
Indicates the primary category or kind of trade activity that characterizes the relationship between the involved entities.
-
C.
productsTraded
Indicates that one entity exchanges or deals specific goods or commodities with another entity.
-
D.
commodityType
Indicates the classification of a good or product according to its type or category within a commodity system.
-
E.
languageUsedInTrade
Indicates that a particular language is employed as a medium of communication in trade or commercial transactions between parties.
- 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_69d8278ed42c8190b9f882dcce611347 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de883bf71c8190a9a092a025cf98f0 |
completed | April 14, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69de2a9515f4819081aabf251bca5878 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:13 a.m.