Triple
T26966066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DDD |
E679174
|
entity |
| Predicate | tacticalDesignConcept |
P161735
|
FINISHED |
| Object | aggregate root |
—
|
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: aggregate root | Statement: [DDD, tacticalDesignConcept, aggregate root]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tacticalDesignConcept Context triple: [DDD, tacticalDesignConcept, aggregate root]
-
A.
tacticalPurpose
Indicates the specific tactical objective or intended operational role that an action, asset, or decision is meant to achieve within a broader plan or mission.
-
B.
tacticalSystem
Indicates a relationship where an entity functions as or is associated with a tactical system used for planning, coordinating, or executing tactical operations.
-
C.
tacticalStyle
Indicates the characteristic way in which an entity plans and executes actions or maneuvers to achieve its objectives.
-
D.
turretDesign
Indicates a relationship where one entity specifies or defines the design or configuration of a turret associated with another entity.
-
E.
tacticalIssue
Indicates a relationship where an entity is involved in, affected by, or characterized as a specific tactical problem, challenge, or concern within an operational 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_69eeeb4f3a448190b1e94b2d4776c16e |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f621210b788190ab9e910cd635f366 |
completed | May 2, 2026, 4:06 p.m. |
| PD | Predicate disambiguation | batch_69f61b3ee7b08190a0a1bc5d26b757aa |
completed | May 2, 2026, 3:41 p.m. |
| PDg | Predicate description generation | batch_69f61f109ef48190873bfe18638d2046 |
completed | May 2, 2026, 3:58 p.m. |
Created at: April 27, 2026, 6:35 a.m.