Triple
T19171033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanije fortress |
E469319
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Kanije |
—
|
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: Kanije | Statement: [Kanije fortress, locatedIn, Kanije]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kanije Context triple: [Kanije fortress, locatedIn, Kanije]
-
A.
Kanije
chosen
Kanije is a historic fortress town in present-day southwestern Hungary that was a key strategic stronghold during the Ottoman–Habsburg conflicts.
-
B.
Kanie
Kanie is a small town in central Japan known for its residential communities and proximity to the city of Nagoya in Aichi Prefecture.
-
C.
Kankia
Kankia is a town and local government area in northern Nigeria, known for its role as an administrative and commercial center within Katsina State.
-
D.
Kaindy
Kaindy is a town in northern Kyrgyzstan that serves as an important urban center within the Chuy Region.
-
E.
Kankinara
Kankinara is a suburban locality in West Bengal, India, known for its railway station on the Kolkata suburban network and its surrounding residential and industrial areas.
- 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_69d8dd09d5a081909ae43c286651ae5a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f163c5888190b4880471d17b4f51 |
completed | April 20, 2026, 9:26 a.m. |
Created at: April 10, 2026, 12:06 p.m.