Triple
T5150123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 20th Maine Volunteer Infantry Regiment |
E116171
|
entity |
| Predicate | casualtiesAtGettysburg |
P35438
|
FINISHED |
| Object | over 30 percent of engaged strength |
—
|
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: over 30 percent of engaged strength | Statement: [20th Maine Volunteer Infantry Regiment, casualtiesAtGettysburg, over 30 percent of engaged strength]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesAtGettysburg Context triple: [20th Maine Volunteer Infantry Regiment, casualtiesAtGettysburg, over 30 percent of engaged strength]
-
A.
confederateCasualtiesAndLosses
Indicates the number or extent of casualties and material losses suffered by Confederate forces in a conflict or engagement.
-
B.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
C.
UScasualties
Indicates the number or occurrence of casualties suffered by the United States in a given conflict, event, or situation.
-
D.
casualtiesAssociatedWithEvent
chosen
Indicates that certain casualties (deaths or injuries) are linked to, or resulted from, a specific event.
-
E.
casualtiesEstimate
Indicates an estimated number of people killed, injured, or otherwise harmed as a result of an event or incident.
- 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_69bd4446c0e08190a7c29dc74976bf03 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd78d7f4d081908d59adcd86f52f1d |
completed | March 20, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69bd77ae2f10819098bb8939106e1281 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:43 p.m.