Triple
T24978597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marblehead Regiment |
E625096
|
entity |
| Predicate | hadLanguageDiversity |
P158152
|
FINISHED |
| Object | included African American soldiers |
—
|
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: included African American soldiers | Statement: [Marblehead Regiment, hadLanguageDiversity, included African American soldiers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadLanguageDiversity Context triple: [Marblehead Regiment, hadLanguageDiversity, included African American soldiers]
-
A.
languageDiversity
Indicates the degree to which multiple distinct languages are present and used within a given context or population.
-
B.
hasLinguisticVariety
Indicates that one entity possesses or exhibits a particular linguistic variety in relation to another entity or context.
-
C.
hasMulticulturalTradition
Indicates that an entity possesses customs, practices, or heritage derived from or influenced by multiple cultural backgrounds.
-
D.
hasMajorityLanguageHistorically
Indicates that a particular language has historically been the predominant or majority language within a given entity or region.
-
E.
historicalDiversity
Indicates that there has been variation or change in the composition, characteristics, or representation of something across different historical periods.
- 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_69e2ff254570819093d197b1900305ac |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f464b4c9b0819085daa00c7c3b8b76 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f45cfb53f4819099bba48c5057e787 |
completed | May 1, 2026, 7:57 a.m. |
| PDg | Predicate description generation | batch_69f464ae42e88190b3549fdf4e0b425e |
completed | May 1, 2026, 8:30 a.m. |
Created at: April 18, 2026, 6:02 a.m.