Triple
T5396543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Discourses on Livy |
E120669
|
entity |
| Predicate | focusOfBook3 |
P34304
|
FINISHED |
| Object | decline and corruption of republics |
—
|
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: decline and corruption of republics | Statement: [Discourses on Livy, focusOfBook3, decline and corruption of republics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusOfBook3 Context triple: [Discourses on Livy, focusOfBook3, decline and corruption of republics]
-
A.
book2Focus
Indicates that attention, interest, or emphasis is directed toward a particular book.
-
B.
book4Focus
Indicates that something is the primary subject or focal point of a book or written work.
-
C.
book5Content
Indicates that one entity is the content or textual material contained within the book represented by the other entity.
-
D.
book3Subject
chosen
Indicates that an entity serves as the third subject or topic discussed or treated in a particular book.
-
E.
book3Title
Indicates the title assigned to the third book in a sequence or collection associated with an entity.
- 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_69bd4637b92c8190b815b6443ae4b323 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8932b8bc8190bd31e11b167a7212 |
completed | March 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69bd84660ea08190a641084814fcf94d |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:04 p.m.