Triple
T5150098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 20th Maine Volunteer Infantry Regiment |
E116171
|
entity |
| Predicate | musteredIntoService |
P61846
|
FINISHED |
| Object | 1862 |
—
|
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: 1862 | Statement: [20th Maine Volunteer Infantry Regiment, musteredIntoService, 1862]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: musteredIntoService Context triple: [20th Maine Volunteer Infantry Regiment, musteredIntoService, 1862]
-
A.
enlistedIn
Indicates that an individual has formally joined and is serving in a particular military or service organization.
-
B.
ageAtEnlistment
Indicates the age a person was when they enlisted in a service, organization, or role.
-
C.
placeOfMilitaryService
Indicates the location or institution where a person performed their military service.
-
D.
militaryUnitTypeServed
Indicates that an entity served in, or was a member of, a specific type of military unit.
-
E.
hadMilitaryObligationsTo
Indicates that one party was bound by duty or law to provide military service, support, or protection to another party.
- 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_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. |
| PDg | Predicate description generation | batch_69bd78d6a1388190804dcf568ca92129 |
completed | March 20, 2026, 4:41 p.m. |
Created at: March 20, 2026, 1:43 p.m.