Triple
T19823772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bulolo Valley |
E476264
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Wau |
—
|
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: Wau | Statement: [Bulolo Valley, hasSettlement, Wau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wau Context triple: [Bulolo Valley, hasSettlement, Wau]
-
A.
Wau
Wau is a major city in northwestern South Sudan that serves as an important administrative, commercial, and transport hub.
-
B.
Wau
chosen
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.
Wana
Wana is a town in Pakistan’s Khyber Pakhtunkhwa province that serves as a key administrative and commercial center in the South Waziristan region.
-
D.
Wana
"Wana" is a popular song by Tanzanian singer Zuchu, known for its catchy Bongo Flava style and romantic themes.
-
E.
Ouakam
Ouakam is a coastal district of Dakar, Senegal, known for its historic fishing community, military installations, and prominent location beneath the African Renaissance Monument.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6550070c4819099e1f057b9a8849e |
completed | April 20, 2026, 4:32 p.m. |
Created at: April 10, 2026, 1:50 p.m.