Triple
T2276138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Falasha |
E50774
|
entity |
| Predicate | relatedToTopic |
P37
|
FINISHED |
| Object | history of Ethiopian Jewry |
—
|
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: history of Ethiopian Jewry | Statement: [Falasha, relatedToTopic, history of Ethiopian Jewry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedToTopic Context triple: [Falasha, relatedToTopic, history of Ethiopian Jewry]
-
A.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
B.
relatedField
Indicates that one field, topic, or area of study is connected or relevant to another in subject matter or application.
-
C.
relatedRFC
Indicates that one resource or specification is connected or associated with another through a shared or relevant RFC (Request for Comments) document.
-
D.
frequentlyDiscussedIn
Indicates that a topic, subject, or entity is often the focus of conversation, debate, or mention within a particular context or medium.
-
E.
relatedTest
Indicates that there exists some form of connection or association between one test and another.
- 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_69a88b05910c8190a9a2b1ff230c85f9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc39c6ff0819081a07696f1c29990 |
completed | March 7, 2026, 6:20 a.m. |
| PD | Predicate disambiguation | batch_69abbdb7719081909143efa8f48df4e4 |
completed | March 7, 2026, 5:55 a.m. |
Created at: March 4, 2026, 7:48 p.m.