Triple
T10590863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hotchkiss gun |
E249982
|
entity |
| Predicate | roleAtWoundedKnee |
P94804
|
FINISHED |
| Object | fired into encampment of Lakota Sioux |
—
|
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: fired into encampment of Lakota Sioux | Statement: [Hotchkiss gun, roleAtWoundedKnee, fired into encampment of Lakota Sioux]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleAtWoundedKnee Context triple: [Hotchkiss gun, roleAtWoundedKnee, fired into encampment of Lakota Sioux]
-
A.
roleAtGettysburg
Indicates the specific role, position, or function an entity held in relation to the Battle of Gettysburg.
-
B.
roleInGoldRush
Indicates that an entity played a specific role or had a particular involvement in the historical event known as the Gold Rush.
-
C.
roleInMexicanAmericanWar
Indicates that an entity participated in the Mexican–American War in a specified capacity or function.
-
D.
roleDuringBlackHawkWar
Indicates the specific role, position, or function an entity held during the Black Hawk War.
-
E.
roleInKoreanWar
Indicates the specific function, position, or involvement an entity had during the Korean War.
- 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_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. |
| PDg | Predicate description generation | batch_69d5270eca0481908573b698390c5b08 |
completed | April 7, 2026, 3:47 p.m. |
Created at: April 6, 2026, 12:40 p.m.