Triple
T549757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hannibal |
E11810
|
entity |
| Predicate | usedMilitaryFormation |
P15598
|
FINISHED |
| Object | double envelopment |
—
|
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: double envelopment | Statement: [Hannibal, usedMilitaryFormation, double envelopment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedMilitaryFormation Context triple: [Hannibal, usedMilitaryFormation, double envelopment]
-
A.
navalFormation
Indicates a relationship where multiple naval units are organized into a coordinated tactical or operational group.
-
B.
militaryOrganization
Indicates that an entity functions as, or is associated with, a structured armed forces or defense-related organization.
-
C.
garrisonDuringFormation
Indicates that a military unit is stationed in a specific garrison location during its period of formation or initial organization.
-
D.
groundForces
Indicates that one entity deploys, commands, or involves military forces operating on land in relation to another entity or context.
-
E.
militaryFunction
Indicates a relationship where an entity serves a specific role, duty, or operational purpose within a military 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49901e4e481909a5ed93c21ab37bd |
completed | March 1, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69a494bae210819093c2e0d33a8ca51a |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a49858abd48190bd4b002a93e4a908 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:32 p.m.