Triple
T11790264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Supernumerary Police |
E280368
|
entity |
| Predicate | providedTrainingFor |
P40765
|
FINISHED |
| Object | future Haganah members |
—
|
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: future Haganah members | Statement: [Supernumerary Police, providedTrainingFor, future Haganah members]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: providedTrainingFor Context triple: [Supernumerary Police, providedTrainingFor, future Haganah members]
-
A.
receivedTrainingIn
Indicates that one entity has undergone or been provided with training or instruction in a particular field, skill, or subject associated with another entity.
-
B.
providesTrainingFor
chosen
Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge of another entity.
-
C.
trainingProvidedAt
Indicates that a training activity or program is conducted or delivered at a specific location or venue.
-
D.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
E.
leadsToTrainingAt
Indicates that one entity causes, results in, or serves as a pathway to another entity undergoing training.
- 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_69d6ab258b808190b1735835c841e3a4 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a587c2d881909297c3a6c7d26080 |
completed | April 10, 2026, 7:23 a.m. |
| PD | Predicate disambiguation | batch_69d8a2491f048190853239bc05090bf4 |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:42 p.m.