Triple
T25388121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1st Squadron, 3rd Cavalry Regiment |
E631579
|
entity |
| Predicate | isBattalionEquivalent |
P158258
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [1st Squadron, 3rd Cavalry Regiment, isBattalionEquivalent, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isBattalionEquivalent Context triple: [1st Squadron, 3rd Cavalry Regiment, isBattalionEquivalent, yes]
-
A.
hasBattalion
Indicates that one entity possesses, commands, or is organizationally assigned a specific battalion.
-
B.
hasBattalionStructure
Indicates that an entity is organized into or associated with a battalion-level military structure.
-
C.
hasBattalionType
Indicates that an entity (such as a military unit) is associated with or classified by a specific type of battalion.
-
D.
hasBattalionNumber
Indicates that an entity (such as a military unit) is associated with a specific battalion number identifier.
-
E.
numberOfBattalions
Indicates the quantitative relationship specifying how many battalions are associated with a given entity or context.
- 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_69e75a8c50788190aabaa9f96710fc43 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f5656d3a04819081b3705ee9d4fd26 |
completed | May 2, 2026, 2:46 a.m. |
| PD | Predicate disambiguation | batch_69f45d0dbc8c8190beecce679fce90a4 |
completed | May 1, 2026, 7:58 a.m. |
| PDg | Predicate description generation | batch_69f464ae42e88190b3549fdf4e0b425e |
completed | May 1, 2026, 8:30 a.m. |
Created at: April 21, 2026, 1:47 p.m.