Triple
T12697721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Ha-Go |
E303378
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Arakan |
E56814
|
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: Arakan | Statement: [Operation Ha-Go, location, Arakan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arakan Context triple: [Operation Ha-Go, location, Arakan]
-
A.
Arakan
chosen
Arakan is a historical coastal region in western Myanmar, now largely corresponding to Rakhine State and known for its distinct ethnic and cultural identity.
-
B.
Thayarwady
Thayarwady is a town in central Myanmar known as an administrative and commercial center within the Bago Region.
-
C.
Magway
Magway is a city in central Myanmar situated on the Irrawaddy River, known as an administrative, commercial, and agricultural hub of the surrounding region.
-
D.
Ta’ang
Ta’ang is a Mon–Khmer language spoken primarily by the Ta’ang (Palaung) ethnic group in parts of Myanmar and neighboring regions.
-
E.
Rakhine State
Rakhine State is a coastal region in western Myanmar known for its ethnically diverse population, including the persecuted Rohingya Muslim minority, and a long history of political and communal conflict.
- 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_69d7bdef90d48190b46b88270e780946 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ed26588190ae76ff17159e06ec |
completed | April 10, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f67c7c4c608190a1786accf8d86141 |
completed | May 2, 2026, 10:36 p.m. |
Created at: April 9, 2026, 5:22 p.m.