Triple
T612896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Romani |
E12137
|
entity |
| Predicate | arrivalInEurope |
P17111
|
FINISHED |
| Object | by late Middle Ages |
—
|
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: by late Middle Ages | Statement: [Romani, arrivalInEurope, by late Middle Ages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: arrivalInEurope Context triple: [Romani, arrivalInEurope, by late Middle Ages]
-
A.
placeOfArrival
Indicates the location at which an entity or person arrives at the end of a journey, movement, or transfer.
-
B.
adoptedEuro
Indicates that a country or entity has officially adopted the euro as its legal currency.
-
C.
yearOfEmigration
Indicates the specific year in which an entity permanently left its country or place of origin to settle elsewhere.
-
D.
europeanRegion
Indicates that an entity is located in, associated with, or classified as part of a region within Europe.
-
E.
passengerTrafficRankInEurope
Indicates the relative position of an entity in Europe based on the volume of passenger traffic it handles.
- F. None of above. chosen
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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49e08dbf88190ab050078a63e266b |
completed | March 1, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69a49cfa7b4481909bec7a5fd3e98c65 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49def31ec81909dc53e70f4a36eda |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:35 p.m.