Triple
T7632886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1st Massachusetts Cavalry |
E172798
|
entity |
| Predicate | casualtiesKilledOrMortallyWounded |
P62746
|
FINISHED |
| Object | approximately 6 officers and 93 enlisted men |
—
|
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: approximately 6 officers and 93 enlisted men | Statement: [1st Massachusetts Cavalry, casualtiesKilledOrMortallyWounded, approximately 6 officers and 93 enlisted men]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesKilledOrMortallyWounded Context triple: [1st Massachusetts Cavalry, casualtiesKilledOrMortallyWounded, approximately 6 officers and 93 enlisted men]
-
A.
casualtiesKilledAndMortallyWounded
chosen
Indicates that the relationship records the number of individuals who were killed outright or died later from mortal wounds.
-
B.
killedOrMortallyWounded
Indicates that one entity caused the death of, or inflicted injuries certain to result in the death of, another entity.
-
C.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
D.
casualtiesTotal
Indicates the total number of people killed and injured as a result of a particular event or incident.
-
E.
casualtiesType
Indicates the specific category or nature of casualties (e.g., killed, injured, missing) associated with 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_69c69952849881908fdcea7a93bfc307 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6faa5f4f08190a7e5259a1b6fb576 |
completed | March 27, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e8cadc8190b7977fcd213954dd |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:57 p.m.