Triple
T2101749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Digenis Akritas |
E37105
|
entity |
| Predicate | heroOrigin |
P34184
|
FINISHED |
| Object | mixed Byzantine and Arab descent |
—
|
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: mixed Byzantine and Arab descent | Statement: [Digenis Akritas, heroOrigin, mixed Byzantine and Arab descent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: heroOrigin Context triple: [Digenis Akritas, heroOrigin, mixed Byzantine and Arab descent]
-
A.
protagonistOrigin
Indicates that one entity is the origin, source, or starting point of the protagonist in a narrative or story.
-
B.
characterOrigin
chosen
Indicates the source, background, or initial context from which a character originates.
-
C.
hasOriginStoryLocation
Indicates that an entity’s origin story takes place at or is associated with a specific location.
-
D.
committeeOfOrigin
Indicates the committee in which a proposal, bill, or item was first introduced or initially considered.
-
E.
eraCharacter
Indicates that a character is associated with, or belongs to, a particular historical or fictional era.
- 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_69a8861828948190924aa30c08806b3a |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abbabc83a8819091f786f21d33b5a6 |
completed | March 7, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69abb7b7b6288190afa11b4d93bd5666 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.