Triple
T10590729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wounded Knee Creek |
E249979
|
entity |
| Predicate | hasHistoricalEventYear |
P2107
|
FINISHED |
| Object | 1890 |
—
|
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: 1890 | Statement: [Wounded Knee Creek, hasHistoricalEventYear, 1890]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricalEventYear Context triple: [Wounded Knee Creek, hasHistoricalEventYear, 1890]
-
A.
hasHistoricalEvent
chosen
Indicates that a historical event occurred in, is associated with, or is relevant to a particular entity.
-
B.
hasHistoricalOriginInYear
Indicates that something first originated, began, or came into existence in a specified calendar year.
-
C.
hasYearOfNamesakeEvent
Indicates the specific year in which the event that a namesake is based on or named after took place.
-
D.
yearOfEventSupport
Indicates the specific year in which support for a particular event occurred or was provided.
-
E.
hasHistoricSignificanceFor
Indicates that something holds notable historical importance or relevance for a particular entity or group.
- 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_69d381c9d3d48190a29ee491e1696a0e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5277b66448190b668c47fe6af4f3d |
completed | April 7, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69d51907b2b881908ab9a8594688ee06 |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:40 p.m.