Triple
T19793501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiger Hill |
E475479
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Gusu District |
—
|
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: Gusu District | Statement: [Tiger Hill, locatedIn, Gusu District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gusu District Context triple: [Tiger Hill, locatedIn, Gusu District]
-
A.
Gusu District
chosen
Gusu District is the central urban district of Suzhou, China, known for its historic canals, classical gardens, and well-preserved ancient cityscape.
-
B.
Govuro District
Govuro District is an administrative district located in Inhambane Province in southern Mozambique.
-
C.
Rorya District
Rorya District is an administrative district in northern Tanzania, located within the Mara Region near the shores of Lake Victoria.
-
D.
Shinkay District
Shinkay District is an administrative district located in Zabul Province in southern Afghanistan.
-
E.
Ivanava District
Ivanava District is an administrative district in the Brest Region of southwestern Belarus, known for its rural settlements and small towns such as Motal.
- 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_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e653c4a8a88190afc2f2cd1ebbbe1e |
completed | April 20, 2026, 4:26 p.m. |
Created at: April 10, 2026, 1:49 p.m.