Triple
T20102121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buna |
E496570
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Sanananda |
—
|
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: Sanananda | Statement: [Buna, locatedNear, Sanananda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sanananda Context triple: [Buna, locatedNear, Sanananda]
-
A.
Sanananda
chosen
Sanananda is a village on the northern coast of Papua New Guinea that was a key World War II battleground during the New Guinea campaign.
-
B.
Sankar
Sankar is a common Indian given name and surname, often associated with Hindu cultural and religious traditions.
-
C.
Nanddas
Nanddas was a prominent 16th-century devotional poet of the Pushtimarg tradition, celebrated for his Braj-language compositions praising Krishna.
-
D.
Sudharak
Sudharak was a Marathi-language social reformist periodical associated with progressive thinker Gopal Ganesh Agarkar, known for advocating rationalism and social change in late 19th-century India.
-
E.
Srikanta
Srikanta is a classic Bengali novel by Sarat Chandra Chattopadhyay that explores the emotional and social struggles of its introspective protagonist against the backdrop of early 20th-century Bengal.
- 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66670a5b48190afe06c8a582bba3d |
completed | April 20, 2026, 5:46 p.m. |
Created at: April 11, 2026, 11:27 p.m.