Triple
T1309827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Special Operations Executive |
E27962
|
entity |
| Predicate | hasTrainingSpecialty |
P24513
|
FINISHED |
| Object | demolition and explosives |
—
|
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: demolition and explosives | Statement: [Special Operations Executive, hasTrainingSpecialty, demolition and explosives]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrainingSpecialty Context triple: [Special Operations Executive, hasTrainingSpecialty, demolition and explosives]
-
A.
hasSpecialty
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
-
B.
trainedAs
Indicates that one entity has received education or instruction to perform the role, profession, or function represented by another entity.
-
C.
hasTrainingType
chosen
Indicates that an entity is associated with or characterized by a specific type or category of training.
-
D.
hasSpecialProcedure
Indicates that a particular entity is associated with or governed by a designated special procedure or process.
-
E.
hasPracticeFields
Indicates that an entity possesses or is associated with one or more designated fields or areas used for practice activities.
- 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_69a496d7d83481908f83085854e51328 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c15490a88190872c3d2698a8f9c9 |
completed | March 1, 2026, 10:44 p.m. |
| PD | Predicate disambiguation | batch_69a4bee9e4a88190b22ab2ee831a23c9 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.