Triple
T10632613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Waziristan Agency |
E250494
|
entity |
| Predicate | largestTown |
P235
|
FINISHED |
| Object | Wana |
E876356
|
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: Wana | Statement: [South Waziristan Agency, largestTown, Wana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wana Context triple: [South Waziristan Agency, largestTown, Wana]
-
A.
Wana
chosen
Wana is a town in Pakistan’s Khyber Pakhtunkhwa province that serves as a key administrative and commercial center in the South Waziristan region.
-
B.
Wau
Wau is a town in Papua New Guinea historically notable as the site of a significant World War II battle between Allied and Japanese forces.
-
C.
Waiyana
Waiyana is an alternative name for the Wayana language, an indigenous Cariban language spoken by the Wayana people in parts of Brazil, Suriname, and French Guiana.
-
D.
Suawa
Suawa is an Austronesian language spoken by the Suwawa people of North Sulawesi, Indonesia.
-
E.
Bawi
Bawi was a Sasanian Persian military commander known for leading forces against the Byzantine Empire during the Iberian War in the 6th century.
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6df95f5e88190b34ce3ec972759ef |
completed | April 8, 2026, 11:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d97a3e0e1481909c277be4c12b46ea |
completed | April 10, 2026, 10:31 p.m. |
Created at: April 8, 2026, 9:02 p.m.