Triple
T16170363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Middle Juba |
E392417
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Hiran |
—
|
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: Hiran | Statement: [Middle Juba, borderedBy, Hiran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hiran Context triple: [Middle Juba, borderedBy, Hiran]
-
A.
Hiran
chosen
Hiran is a central region of Somalia known for its strategic location along the Shabelle River and its role as an important agricultural and administrative area.
-
B.
Haruna
Haruna was a Japanese Kongō-class fast battleship that served in the Imperial Japanese Navy during both World Wars and saw extensive action in the Pacific Theater.
-
C.
Hiranaka
Hiranaka is a Japanese surname borne by individuals such as former professional boxer Akinobu Hiranaka.
-
D.
Yahata
Yahata was a former city in Fukuoka Prefecture, Japan, that became part of the larger city of Kitakyushu through municipal merger.
-
E.
Hara
Hara is a Japanese surname borne by various notable figures in politics, arts, and sports.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21eb6de30819083af54b50ae5ae51 |
completed | April 17, 2026, 11:51 a.m. |
Created at: April 10, 2026, 5:02 a.m.