Triple
T9442753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Venusia |
E227686
|
entity |
| Predicate | colonistsNumber |
P78459
|
FINISHED |
| Object | 20000 Roman colonists |
—
|
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: 20000 Roman colonists | Statement: [Venusia, colonistsNumber, 20000 Roman colonists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colonistsNumber Context triple: [Venusia, colonistsNumber, 20000 Roman colonists]
-
A.
colonistsIncluded
Indicates that colonists are counted as part of, or explicitly included within, a specified group, set, or context.
-
B.
representedColony
Indicates that an entity acted as an official representative or delegate for a particular colony in some context or event.
-
C.
numberOfColonies
Indicates the count of distinct colonies associated with or possessed by a given entity.
-
D.
numberOfInitialSettlers
chosen
Indicates the quantity of settlers present at the initial establishment of a settlement or colony.
-
E.
numberOfColoniesRepresented
Indicates the count of distinct colonies that are represented or involved in relation to a given entity or context.
- 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_69ca843884488190ad6cbe0153088234 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f300cc88190a793712706295c53 |
completed | April 1, 2026, 8:25 p.m. |
| PD | Predicate disambiguation | batch_69cca5596ffc819097e9c8eefd4ef9b8 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:50 p.m.