Triple
T16955073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maʻopūtasi County |
E411277
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Masefau |
E1151326
|
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: Masefau | Statement: [Maʻopūtasi County, contains, Masefau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Masefau Context triple: [Maʻopūtasi County, contains, Masefau]
-
A.
Masefau
chosen
Masefau is a coastal village in American Samoa located on the island of Tutuila.
-
B.
Mazirbe
Mazirbe is a coastal village in Latvia known as a historic cultural hub of the Livonian people and their language.
-
C.
Maleka
Maleka is a feminine given name, typically considered a variant spelling of Malika and used in various cultures.
-
D.
Mafadi
Mafadi is a prominent mountain peak on the border of South Africa and Lesotho, renowned as the highest point in South Africa and a popular destination for serious hikers and mountaineers.
-
E.
Mazabuka
Mazabuka is a town in southern Zambia known for its sugar industry and agricultural production.
- 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.