Triple
T35299641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lorenz cipher |
E1019468
|
entity |
| Predicate | brokenUsing |
P182703
|
FINISHED |
| Object | statistical analysis |
—
|
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: statistical analysis | Statement: [Lorenz cipher, brokenUsing, statistical analysis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brokenUsing Context triple: [Lorenz cipher, brokenUsing, statistical analysis]
-
A.
brokenIn
Indicates that an object or system has become nonfunctional or damaged while located within or inside a particular place, context, or container.
-
B.
broken
Indicates that an entity is damaged or no longer functioning as intended, often as the result of some prior action or event.
-
C.
brokenBy
Indicates that one entity causes the damage, destruction, or loss of functionality of another entity.
-
D.
brokenOn
Indicates that an object or system ceased functioning or became damaged at a specific time or on a specific date.
-
E.
broke
Indicates that one entity caused another entity to separate into pieces or cease functioning, typically through force or damage.
- 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_69f76de7eedc8190a3bdc64ebbc05b42 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7904a770481908ef3f788e51e8dba |
completed | May 3, 2026, 6:13 p.m. |
| PD | Predicate disambiguation | batch_69f78e2f52e08190a77661223a96c601 |
completed | May 3, 2026, 6:04 p.m. |
| PDg | Predicate description generation | batch_69f78f629d508190b755848162c4e101 |
completed | May 3, 2026, 6:09 p.m. |
Created at: May 3, 2026, 4:03 p.m.