Triple
T3772231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western Saudi Arabia |
E83223
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Umluj |
E235403
|
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: Umluj | Statement: [Western Saudi Arabia, containsCity, Umluj]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Umluj Context triple: [Western Saudi Arabia, containsCity, Umluj]
-
A.
Umluj
chosen
Umluj is a coastal town in northwestern Saudi Arabia on the Red Sea, known for its pristine beaches and islands that have earned it the nickname "the Maldives of Saudi Arabia."
-
B.
Ngizim
Ngizim is a West Chadic language spoken primarily by the Ngizim people in northeastern Nigeria.
-
C.
Kasulu
Kasulu is a town in western Tanzania that serves as one of the main urban and commercial centers of the Kigoma Region.
-
D.
Ummanz
Ummanz is a small German Baltic Sea island located just off the western coast of Rügen, known for its rural landscape and bird-rich wetlands.
-
E.
Lomwe
Lomwe is a Bantu language spoken primarily in Mozambique and Malawi by the Lomwe people.
- 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_69ad8b235e608190b5a2b1d1bfcef50b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc3219b881908a2f82126f9a679d |
completed | March 8, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e52bb2d08190b457dd517ff366d7 |
completed | March 14, 2026, 4:33 a.m. |
Created at: March 8, 2026, 3:36 p.m.