Triple
T652320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flavius Josephus |
E11369
|
entity |
| Predicate | wroteForAudience |
P10804
|
FINISHED |
| Object | Greco-Roman readers |
—
|
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: Greco-Roman readers | Statement: [Flavius Josephus, wroteForAudience, Greco-Roman readers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wroteForAudience Context triple: [Flavius Josephus, wroteForAudience, Greco-Roman readers]
-
A.
originallyWrittenFor
Indicates that a work was initially created or composed with a particular recipient, medium, context, or purpose in mind.
-
B.
hasWrittenFor
Indicates that one entity has created written content (such as articles, stories, or texts) for or on behalf of another entity, typically a publication, organization, or platform.
-
C.
writtenIn
Indicates that a work (such as a text, program, or document) is expressed or encoded using a particular language or notation.
-
D.
typicalAudience
chosen
Indicates the group of people for whom something (such as a work, product, or resource) is primarily intended or most suitable.
-
E.
wroteIn
Indicates that an entity authored or composed something using a particular language, medium, or writing system.
- 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f35acb08190a3a8248023ce07f9 |
completed | March 1, 2026, 8:19 p.m. |
| PD | Predicate disambiguation | batch_69a49d1001088190aa7ca3c8f2ad0e32 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.