Triple
T31450187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abuna of Ethiopia |
E802300
|
entity |
| Predicate | traditionallyNonEthiopian |
P196631
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Abuna of Ethiopia, traditionallyNonEthiopian, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionallyNonEthiopian Context triple: [Abuna of Ethiopia, traditionallyNonEthiopian, true]
-
A.
traditionallyOneOf
Indicates that something is customarily or historically considered to belong to a specific set, category, or group.
-
B.
traditionallyUsedBy
Indicates that something has been customarily or historically used by a particular person, group, or culture over time.
-
C.
languageTraditionally
Indicates that something is customarily or historically expressed, written, or communicated in a particular language.
-
D.
traditionalOrigin
Indicates that something comes from, or is rooted in, a long-established cultural or customary source or practice.
-
E.
isTraditionalInCountry
Indicates that something is customary, long-established, or commonly practiced within a particular country.
- 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_69f348c5a6bc819092a557e95438976f |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe5ec9028081909ae3d6fbe2f4cbbc |
completed | May 8, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69fe5e1d715881909fc516fafc707644 |
completed | May 8, 2026, 10:05 p.m. |
| PDg | Predicate description generation | batch_69fe5ec84910819094cb15269ace7c51 |
completed | May 8, 2026, 10:08 p.m. |
Created at: April 30, 2026, 9:12 p.m.