Triple
T7557406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 26th Yankee Brigade |
E178702
|
entity |
| Predicate | hasBattalionType |
P77603
|
FINISHED |
| Object | infantry battalion |
—
|
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: infantry battalion | Statement: [26th Yankee Brigade, hasBattalionType, infantry battalion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBattalionType Context triple: [26th Yankee Brigade, hasBattalionType, infantry battalion]
-
A.
hasBattalion
Indicates that one entity possesses, commands, or is organizationally assigned a specific battalion.
-
B.
hasBattalionNumber
Indicates that an entity (such as a military unit) is associated with a specific battalion number identifier.
-
C.
numberOfBattalions
Indicates the quantitative relationship specifying how many battalions are associated with a given entity or context.
-
D.
regimentalCategory
Indicates the classification or type of regiment to which a military unit or formation belongs.
-
E.
hasRegimentalIdentity
Indicates that an entity possesses or is associated with a specific regimental identity, such as belonging to or being characterized by a particular regiment.
- 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_69c69f2da22c8190a50942ac20af70e8 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8db3d508190850ed41854d69838 |
completed | March 27, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69c6f4dc485c819080da13e3b7f4f08f |
completed | March 27, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69c6f59517648190ac0a9e9cba045dd5 |
completed | March 27, 2026, 9:24 p.m. |
Created at: March 27, 2026, 3:50 p.m.