Triple
T300810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Hawk |
E6193
|
entity |
| Predicate | yearOfCapture |
P5050
|
FINISHED |
| Object | 1832 |
—
|
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: 1832 | Statement: [Black Hawk, yearOfCapture, 1832]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearOfCapture Context triple: [Black Hawk, yearOfCapture, 1832]
-
A.
capturedYear
chosen
Indicates the year in which an entity was captured or taken into custody.
-
B.
commissionedYear
Indicates the year in which something (typically a work, project, or item) was formally ordered, authorized, or put into production.
-
C.
capturedBy
Indicates that one entity has been seized, taken into control, or otherwise apprehended by another entity.
-
D.
capturedDuring
Indicates that one event or state occurred within the temporal span of another, typically representing that something was recorded, seized, or documented while a specific situation or activity was taking place.
-
E.
originYear
Indicates the year in which something first originated, was created, or began.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea2fba548190a5aeb1597dca96bd |
completed | Feb. 28, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69a2e93aff048190a633c8ae2b76a41f |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.