Triple
T3001297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Babylonian Chronicles |
E81792
|
entity |
| Predicate | documentsEvent |
P4310
|
FINISHED |
| Object | fall of Nineveh |
—
|
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: fall of Nineveh | Statement: [Babylonian Chronicles, documentsEvent, fall of Nineveh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: documentsEvent Context triple: [Babylonian Chronicles, documentsEvent, fall of Nineveh]
-
A.
documentAtIssue
Indicates that a particular document is the specific item under consideration or dispute in a given context or proceeding.
-
B.
documentNumber
Indicates the unique identifying number assigned to a specific document in the relationship.
-
C.
documentedBy
chosen
Indicates that something is recorded, described, or evidenced in a specific document or set of documents.
-
D.
documentForm
Indicates the specific format or structural type in which a document is presented or recorded.
-
E.
documentModel
Indicates that an entity serves as or is associated with a specific structured representation or schema of a document.
- 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_69ad8b1c4de88190a83b7cefaa1f2842 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a1022e48190afee77db94635ff2 |
completed | March 8, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69ad9615fefc8190ad96da92519cb7a3 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:59 p.m.