Triple
T21829990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masally District |
E538965
|
entity |
| Predicate | administrativeCenter |
P1474
|
FINISHED |
| Object | Masally |
—
|
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: Masally | Statement: [Masally District, administrativeCenter, Masally]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Masally Context triple: [Masally District, administrativeCenter, Masally]
-
A.
Masally
chosen
Masally is a town in southern Azerbaijan that serves as an administrative and economic center for the surrounding region.
-
B.
Maysalun
Maysalun is a mountainous area in southwestern Syria best known as the site of the 1920 Battle of Maysalun between Syrian forces and the French army.
-
C.
Masuleh
Masuleh is a historic stepped village in northern Iran renowned for its terraced architecture built into the mountainside and its scenic foggy landscapes.
-
D.
Masarra
Masarra is a passenger station on Cairo Metro’s Line 2 serving commuters in the Cairo metropolitan area.
-
E.
Molazzana
Molazzana is a small municipality in Tuscany, central Italy, known for its scenic location in the Garfagnana area of the Apennine mountains.
- 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_69e0c475cda88190987d08f23caebdc1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0913554508190b81347f01d3903e8 |
completed | April 28, 2026, 10:51 a.m. |
Created at: April 16, 2026, 6:54 p.m.