Triple
T29361354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ethiopia and Eritrea |
E744598
|
entity |
| Predicate | EthiopiaOfficialLanguages |
P95654
|
FINISHED |
| Object | Amharic |
—
|
NE NERFINISHED |
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: Amharic | Statement: [Ethiopia and Eritrea, EthiopiaOfficialLanguages, Amharic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: EthiopiaOfficialLanguages Context triple: [Ethiopia and Eritrea, EthiopiaOfficialLanguages, Amharic]
-
A.
languageNameAmharic
Indicates that the subject’s language name is expressed in the Amharic language.
-
B.
hasLanguageOfficial
Indicates that a language holds official status within a given entity, such as a country, region, or organization.
-
C.
hasOfficialCountryLanguage
chosen
Indicates that a country recognizes a particular language as one of its official languages for governmental or legal purposes.
-
D.
additionalOfficialLanguage
Indicates that an entity has another language, beyond its primary one, that holds official or formally recognized status.
-
E.
haveDistinctOfficialLanguages
Indicates that the two entities each have their own official language and these official languages are not the same.
- 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_69f0a79aee588190b490f19d93c6e52d |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f6698892e88190b076bb0cdf159d8b |
completed | May 2, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69f66339175c819080bd70f0ff7057b1 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 2:18 p.m.