Triple
T16681015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Hetman of the Crown |
E405336
|
entity |
| Predicate | officeProminentInPeriod |
P97182
|
FINISHED |
| Object | 16th 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: 16th century | Statement: [Grand Hetman of the Crown, officeProminentInPeriod, 16th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeProminentInPeriod Context triple: [Grand Hetman of the Crown, officeProminentInPeriod, 16th century]
-
A.
officeHeldInPeriod
Indicates that an entity held a particular office or position during a specified time period.
-
B.
notableOfficePeriod
Indicates that an entity held a particular office or position during a specified time period.
-
C.
officeHeldDuring
Indicates that a person occupied a specific official position during a particular time period.
-
D.
meetsInTimePeriod
Indicates that two entities encounter or come together during a specified time period.
-
E.
appearsInTimePeriod
chosen
Indicates that an entity is present, active, or occurs within a specified time period.
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d6f5cf481909e7628bbaa884e5a |
completed | April 18, 2026, 12:47 p.m. |
| PD | Predicate disambiguation | batch_69e319bc73908190a0e38bc926b31f10 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:19 a.m.