Triple
T2832489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Iraq |
E62271
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Kut |
E68772
|
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: Kut | Statement: [Southern Iraq, hasMajorCity, Kut]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kut Context triple: [Southern Iraq, hasMajorCity, Kut]
-
A.
Kut
chosen
Kut is a city in eastern Iraq situated on the banks of the Tigris River, known historically as a strategic location and the site of significant World War I battles.
-
B.
Kuta
Kuta is a popular beach resort town in southern Bali, Indonesia, known for its surfing waves, vibrant nightlife, and dense concentration of hotels, shops, and restaurants.
-
C.
Kutelo
Kutelo is one of the highest and most prominent peaks in Bulgaria’s Pirin mountain range, known for its sharp ridges and alpine terrain.
-
D.
Kutaisi
Kutaisi is one of Georgia’s major cities, historically significant and formerly a capital, located in the western part of the country.
-
E.
Kamen
Kamen is a surname most prominently associated with American inventor and entrepreneur Dean Kamen, known for creating the Segway and numerous medical devices.
- 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_69ab4c3c39188190955b9c49d98463d8 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdebe95188190bf65fb4cd88e2ec5 |
completed | March 7, 2026, 8:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afe8bb92b08190b1de7e6973d96301 |
completed | March 10, 2026, 9:47 a.m. |
Created at: March 6, 2026, 10:01 p.m.