Triple
T18618702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shewa |
E455094
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object |
Ankober
Ankober is a historic mountain town in central Ethiopia that once served as a royal seat and key political center of the Shewan kingdom.
|
E1333360
|
NE FINISHED |
How this triple was built (4 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: Ankober | Statement: [Shewa, capital, Ankober]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ankober Context triple: [Shewa, capital, Ankober]
-
A.
Ḍogrī
Ḍogrī is the native name of the Dogri language, an Indo-Aryan language spoken primarily in the Jammu region of India.
-
B.
Ananuri
Ananuri is a historic castle complex in Georgia, renowned for its medieval fortifications and churches overlooking the Aragvi River.
-
C.
Angarano
Angarano is an Italian-origin surname most notably associated with American actor Michael Angarano.
-
D.
Kobuleti
Kobuleti is a Georgian Black Sea resort town known for its long pebble beaches and role as a popular holiday destination in the autonomous region of Adjara.
-
E.
Hadrut
Hadrut is a town in the Nagorno-Karabakh region, historically part of the Shusha uezd, known for its strategic location and role in regional conflicts between Armenia and Azerbaijan.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ankober Triple: [Shewa, capital, Ankober]
Generated description
Ankober is a historic mountain town in central Ethiopia that once served as a royal seat and key political center of the Shewan kingdom.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ankober Target entity description: Ankober is a historic mountain town in central Ethiopia that once served as a royal seat and key political center of the Shewan kingdom.
-
A.
Ḍogrī
Ḍogrī is the native name of the Dogri language, an Indo-Aryan language spoken primarily in the Jammu region of India.
-
B.
Ananuri
Ananuri is a historic castle complex in Georgia, renowned for its medieval fortifications and churches overlooking the Aragvi River.
-
C.
Angarano
Angarano is an Italian-origin surname most notably associated with American actor Michael Angarano.
-
D.
Kobuleti
Kobuleti is a Georgian Black Sea resort town known for its long pebble beaches and role as a popular holiday destination in the autonomous region of Adjara.
-
E.
Hadrut
Hadrut is a town in the Nagorno-Karabakh region, historically part of the Shusha uezd, known for its strategic location and role in regional conflicts between Armenia and Azerbaijan.
- F. None of above. chosen
Provenance (5 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_69d8d38bbe7c8190bdec3138e7d413c9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54d07dc288190bb3b8b5ab06518da |
completed | April 19, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a050390bd4c8190b623f08a12eee39b |
completed | May 13, 2026, 11:04 p.m. |
| NEDg | Description generation | batch_6a050455e6e8819084927b1c2d4a5237 |
completed | May 13, 2026, 11:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0505cbc11481908e61d90dd64f6212 |
completed | May 13, 2026, 11:14 p.m. |
Created at: April 10, 2026, 11:46 a.m.