Triple
T15407325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keffi |
E368492
|
entity |
| Predicate | hasNearbyUrbanCenter |
P36605
|
FINISHED |
| Object | Karu |
E368494
|
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: Karu | Statement: [Keffi, hasNearbyUrbanCenter, Karu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karu Context triple: [Keffi, hasNearbyUrbanCenter, Karu]
-
A.
Karu
chosen
Karu is a local government area in Nasarawa State, Nigeria, known for its proximity to Abuja and rapid urban growth as a residential and commercial hub.
-
B.
Karu
Karu was the personal name of Emperor Monmu, an 8th-century ruler of Japan from the Asuka/Nara period.
-
C.
Karuah
Karuah is a small town in New South Wales, Australia, known for its location on the Karuah River and its fishing and oyster-farming activities.
-
D.
Kashira
Kashira is a historic town in Russia, located south of Moscow on the Oka River and known as a regional industrial and transport center.
-
E.
Kasari
Kasari is a town located on Amami Ōshima in Japan’s Kagoshima Prefecture, known for its subtropical island scenery and coastal environment.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03ea36c6881909eaea48e9608897a |
completed | April 16, 2026, 1:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff135a26f08190ad3fc1d5a263a24e |
completed | May 9, 2026, 10:58 a.m. |
Created at: April 10, 2026, 3:20 a.m.