Triple
T4733646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anseba |
E105070
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Keren |
E392868
|
NE 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: Keren | Statement: [Anseba, capital, Keren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Keren Context triple: [Anseba, capital, Keren]
-
A.
Keren
chosen
Keren is a major town in Eritrea known as an important commercial and agricultural center in the Anseba region.
-
B.
Sharona Katan
Sharona Katan is an Israeli-born visual artist and the wife of Radiohead guitarist and composer Jonny Greenwood.
-
C.
Alona Tal
Alona Tal is an Israeli-American actress and singer known for her roles in television series such as "Veronica Mars," "Supernatural," and "Hand of God."
-
D.
Rachel Dayan
Rachel Dayan was the wife of prominent Israeli military leader and politician Moshe Dayan.
-
E.
Yoni Brenner
Yoni Brenner is a screenwriter and humorist known for his work on animated films, including contributing to the screenplay of "Rio 2."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69bd43ee52048190b81a4f066534ffb3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6467a1fc819089485b4d76e0edc4 |
completed | March 20, 2026, 3:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be10acf7488190946b31f95114d459 |
completed | March 21, 2026, 3:29 a.m. |
Created at: March 20, 2026, 1:19 p.m.