Triple
T14271689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pegu campaign |
E353801
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Pegu |
E276026
|
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: Pegu | Statement: [Pegu campaign, location, Pegu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pegu Context triple: [Pegu campaign, location, Pegu]
-
A.
Pegu
chosen
Pegu is an important historical city in Lower Myanmar that once served as the political and cultural center of the Mon people and a major hub of regional trade and Buddhism.
-
B.
Tajuan
Tajuan is the given first name of former NFL cornerback Ty Law.
-
C.
Pangshura
Pangshura is a genus of South Asian freshwater turtles commonly known as roofed turtles, recognized for the distinctive raised shape of their shells.
-
D.
Pambujan
Pambujan is a coastal municipality in the province of Northern Samar in the Philippines, known for its rural communities and natural landscapes.
-
E.
Praijing
Praijing is a traditional village on Sumba Island in Indonesia, known for its distinctive high-roofed houses and preserved Marapu cultural practices.
- 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_69de65811d7c8190b075909a6570d415 |
completed | April 14, 2026, 4:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd326a5aec8190b139a0c49fd43705 |
completed | May 8, 2026, 12:46 a.m. |
Created at: April 10, 2026, 1:10 a.m.