Triple
T521248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hesse-Kassel |
E10821
|
entity |
| Predicate | troopType |
P6154
|
FINISHED |
| Object | Hessian mercenaries |
—
|
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: Hessian mercenaries | Statement: [Hesse-Kassel, troopType, Hessian mercenaries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: troopType Context triple: [Hesse-Kassel, troopType, Hessian mercenaries]
-
A.
typeOfTroops
chosen
Indicates the specific category or kind of military forces involved in or associated with an entity or event.
-
B.
militaryOrganization
Indicates that an entity functions as, or is associated with, a structured armed forces or defense-related organization.
-
C.
fleetType
Indicates the category or classification of a fleet to which an entity belongs or with which it is associated.
-
D.
squadron
Indicates that an entity is organized into or associated with a specific squadron as a formal operational unit.
-
E.
militaryCharacteristic
Indicates that one entity possesses a specific military-related attribute, quality, or feature in relation to another entity or context.
- F. None of above.
Provenance (3 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1a1817c8190a6cc8f423071d3ad |
completed | Feb. 28, 2026, 1:46 p.m. |
| PD | Predicate disambiguation | batch_69a2f016ba5c81909825b04e7525b4ab |
completed | Feb. 28, 2026, 1:39 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.