Triple
T37154032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vallonia, Indiana |
E920443
|
entity |
| Predicate | settledInPeriod |
P7934
|
FINISHED |
| Object | early 19th century |
—
|
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: early 19th century | Statement: [Vallonia, Indiana, settledInPeriod, early 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settledInPeriod Context triple: [Vallonia, Indiana, settledInPeriod, early 19th century]
-
A.
residencePeriod
Indicates the length of time an entity resides or has resided at a particular location.
-
B.
establishedPeriod
Indicates the time span or date range during which something was founded, created, or formally brought into existence.
-
C.
isSettledIn
Indicates that an entity resides or has established its home or base in a particular location.
-
D.
locationPeriod
chosen
Indicates that an entity is associated with being at a particular location during a specified time period.
-
E.
settledInYear
Indicates the specific calendar year in which an entity became established, inhabited, or formally settled in a particular place or status.
- 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_69f76e9f87c08190b4c8f7fafbd8345a |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb344c60f8819090f2e21e1e61d621 |
completed | May 6, 2026, 12:30 p.m. |
| PD | Predicate disambiguation | batch_69fb2f642db08190b562725502c74ea6 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:15 p.m.