Triple
T67263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Légion d'honneur |
E1340
|
entity |
| Predicate | hasMilitaryDivision |
P4206
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Légion d'honneur, hasMilitaryDivision, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMilitaryDivision Context triple: [Légion d'honneur, hasMilitaryDivision, true]
-
A.
hasMilitaryBranch
Indicates that an entity is associated with, served in, or is part of a specific branch of a military organization.
-
B.
militaryDistrict
Indicates that an entity functions as, or is located within, an administrative military district or region under military jurisdiction.
-
C.
hasMilitaryBase
Indicates that one entity possesses, hosts, or contains a military base associated with or located on another entity.
-
D.
hasCadetBranch
Indicates that one lineage, family, or house is a junior or offshoot branch derived from another main or senior line.
-
E.
involvedUnit
Indicates that a particular unit (such as a group, organization, or division) participates in, is associated with, or plays a role in the referenced event or activity.
- 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a2509b5a088190bb9d2b650aeb8bca |
completed | Feb. 28, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_69a24ea749788190bc17865171ff909a |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a2509a1c088190b4afa3045455709a |
completed | Feb. 28, 2026, 2:19 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.