Triple
T14282549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U Nu |
E354085
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Wakema |
E354085
|
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: Wakema | Statement: [U Nu, placeOfBirth, Wakema]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wakema Context triple: [U Nu, placeOfBirth, Wakema]
-
A.
Wakema
chosen
Wakema is a town in Myanmar’s Ayeyarwady Region, known as the birthplace of former Burmese Prime Minister U Nu.
-
B.
Keila
Keila is a small town in northern Estonia known for its historic church, scenic Keila River and waterfall, and role as a local administrative and transport hub.
-
C.
Kirsha
Kirsha is a central character in Naguib Mahfouz’s novel "Midaq Alley," known as the café owner whose personal life and hidden desires reflect the social and moral tensions of mid-20th-century Cairo.
-
D.
Katisha
Katisha is a formidable, older noblewoman and comic villainess in Gilbert and Sullivan’s operetta "The Mikado," known for her dramatic presence and unrequited love for Nanki-Poo.
-
E.
Wakool
Wakool is a small rural locality in the Riverina region of New South Wales, Australia, known for its agricultural activities and proximity to the Wakool River.
- 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de697d9fd08190b0cd7a6a6737ba03 |
completed | April 14, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3d1884f481908ea266c1651c4b59 |
completed | May 8, 2026, 1:32 a.m. |
Created at: April 10, 2026, 1:10 a.m.