Triple
T16955070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maʻopūtasi County |
E411277
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Amaua |
E1151327
|
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: Amaua | Statement: [Maʻopūtasi County, contains, Amaua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amaua Context triple: [Maʻopūtasi County, contains, Amaua]
-
A.
Amaua
chosen
Amaua is a small village in American Samoa located on the island of Tutuila within the jurisdiction of Pago Pago.
-
B.
Amausi
Amausi is a locality in Lucknow, India, best known for hosting the city’s main airport and associated transport and commercial facilities.
-
C.
Amar'e
Amar'e is a retired American professional basketball player best known as an explosive All-Star power forward in the NBA, primarily with the Phoenix Suns and New York Knicks.
-
D.
Aumale
Aumale is a historic town and former county in Normandy, France, notable for its medieval noble associations.
-
E.
Ama
Ama is a small city located in Aichi Prefecture in Japan, known primarily as a residential and commuter town within the Nagoya metropolitan area.
- 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_69d886c9c9d481909afe222093641cae |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d01bb700819082a441c124be3cb6 |
completed | April 18, 2026, 6:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d464762c8190a734ffdd83633f70 |
completed | May 10, 2026, 6:54 p.m. |
Created at: April 10, 2026, 5:31 a.m.