Triple
T28141455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finstermünz |
E714352
|
entity |
| Predicate | onTradeRouteBetween |
P92966
|
FINISHED |
| Object | Austria and Italy |
—
|
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: Austria and Italy | Statement: [Finstermünz, onTradeRouteBetween, Austria and Italy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: onTradeRouteBetween Context triple: [Finstermünz, onTradeRouteBetween, Austria and Italy]
-
A.
includesTradeRoute
Indicates that one entity contains, encompasses, or makes use of a particular trade route within its scope or structure.
-
B.
usedForTradeBetween
chosen
Indicates that something serves as a medium, instrument, or basis for trade or exchange between two or more parties.
-
C.
tradedAlong
Indicates that an entity engaged in trade or exchange activities following or using a particular route, path, or corridor.
-
D.
tradeAspect
Indicates a relationship where one entity is associated with a specific aspect, feature, or dimension of a trade or commercial transaction.
-
E.
hasCommercialCorridorAlong
Indicates that a place contains a continuous stretch of commercial activity or businesses situated along a specified linear feature, such as a street or route.
- 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_69efd6af156c81908f50c2cd7db0e1ef |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f64135fa1c819095e4919713159969 |
completed | May 2, 2026, 6:23 p.m. |
| PD | Predicate disambiguation | batch_69f63c6a8474819091b8c6fe98e3862d |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 9:53 p.m.