Triple
T36771995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 30th Ohio Infantry Regiment |
E908503
|
entity |
| Predicate | musteredInFor |
P61846
|
FINISHED |
| Object | three years |
—
|
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: three years | Statement: [30th Ohio Infantry Regiment, musteredInFor, three years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: musteredInFor Context triple: [30th Ohio Infantry Regiment, musteredInFor, three years]
-
A.
musteredIn
Indicates that an individual or unit was formally enrolled, assembled, or brought into active service within an organization, typically a military force.
-
B.
musteredIntoService
chosen
Indicates that an entity has been formally enrolled or assembled into active duty or official service under an authority.
-
C.
enlistedIn
Indicates that an individual has formally joined and is serving in a particular military or service organization.
-
D.
enlistedFrom
Indicates that a person joined or was recruited into a military or service organization from a specific place, institution, or prior affiliation.
-
E.
hadMilitia
Indicates that an entity maintained or was associated with a militia force during a certain period.
- 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_69f76e786ba481909cdcf6cf6b39dd32 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c9f5a8848190ba956ff27f44e396 |
completed | May 3, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69f7c8999a348190abc1895eaa6e036d |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:12 p.m.