Triple
T20980036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Captain Frederick Wentworth |
E516732
|
entity |
| Predicate | firstEngagementYear |
P142342
|
FINISHED |
| Object | 1806 |
—
|
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: 1806 | Statement: [Captain Frederick Wentworth, firstEngagementYear, 1806]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstEngagementYear Context triple: [Captain Frederick Wentworth, firstEngagementYear, 1806]
-
A.
firstMeetingYear
Indicates the calendar year in which two entities first met or had their initial encounter.
-
B.
firstCaptureYear
Indicates the year in which an entity was first captured or recorded as captured.
-
C.
firstArrivalYear
Indicates the calendar year in which an entity first arrived at or was initially present in a specified place or context.
-
D.
firstRunningYear
Indicates the year in which something (such as an event, service, or operation) first began running or was initially active.
-
E.
firstAchievedInYear
Indicates the year in which something was first accomplished, attained, or realized.
- 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_69e0b4ffac148190bbade9f0eceb660b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fbdd89f48190b58c67cc1f7968c0 |
completed | April 21, 2026, 4:23 a.m. |
| PD | Predicate disambiguation | batch_69e5dbe6976081908abd4e9c8734bae9 |
completed | April 20, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69e5e2df1a888190b5b478e76bdf7fdf |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 16, 2026, 1:47 p.m.