Triple
T15326263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pago Pago County |
E366418
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Aua |
E74261
|
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: Aua | Statement: [Pago Pago County, contains, Aua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aua Context triple: [Pago Pago County, contains, Aua]
-
A.
Aua
chosen
Aua is a coastal village on the island of Tutuila in American Samoa, known for its traditional Samoan community and proximity to Pago Pago Harbor.
-
B.
Ukaan
Ukaan is a little-documented Niger-Congo language spoken by a small community in southwestern Nigeria.
-
C.
Hau
Hau is the surname of Danish physicist Lene Vestergaard Hau, known for her pioneering work in slowing and stopping light.
-
D.
Aukena
Aukena is a small inhabited island in the Gambier Islands of French Polynesia, known for its historical Catholic mission sites and scenic lagoon setting.
-
E.
Arua
Arua is a major town in northwestern Uganda that serves as an important commercial and transport hub near the borders with the Democratic Republic of the Congo and South Sudan.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03dfd8f048190831b463a2728eafe |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef8add7088190b124bd4727bb2f28 |
completed | May 9, 2026, 9:04 a.m. |
Created at: April 10, 2026, 3:16 a.m.