Triple
T14883021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Bagyidaw |
E350047
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Bagyidaw |
E778449
|
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: Bagyidaw | Statement: [King Bagyidaw, givenName, Bagyidaw]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bagyidaw Context triple: [King Bagyidaw, givenName, Bagyidaw]
-
A.
Bagyidaw
chosen
Bagyidaw was a 19th-century Burmese king of the Konbaung Dynasty, known for his role in the First Anglo-Burmese War and the subsequent decline of the Burmese kingdom.
-
B.
Bongabon
Bongabon is a landlocked agricultural municipality in the province of Nueva Ecija in the Philippines, known for its onion production and mountainous terrain near the Sierra Madre range.
-
C.
Bagabag
Bagabag is a municipality in the Philippine province of Nueva Vizcaya, known as a key agricultural area and gateway to the Ifugao highlands.
-
D.
Bago
Bago is a component city in the province of Negros Occidental in the Philippines, known for its agricultural economy and historical significance.
-
E.
Bago
Bago is a historic city in southern Myanmar known for its ancient Buddhist monuments and proximity to Yangon.
- 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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5e7c0e48190af2d68a71130585c |
completed | April 15, 2026, 12:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b5af8208190a35451477ea20b03 |
completed | May 8, 2026, 11:01 p.m. |
Created at: April 10, 2026, 1:56 a.m.