Triple
T3471123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plateau State |
E73259
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Barkin Ladi |
E337058
|
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: Barkin Ladi | Statement: [Plateau State, hasCity, Barkin Ladi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barkin Ladi Context triple: [Plateau State, hasCity, Barkin Ladi]
-
A.
Barkin Ladi
chosen
Barkin Ladi is a town and local government area in Plateau State, central Nigeria, known for its Berom population and highland agricultural landscape.
-
B.
Laika
Laika is an American stop-motion animation studio renowned for visually distinctive, critically acclaimed films such as Coraline, ParaNorman, and Kubo and the Two Strings.
-
C.
Laika
Laika was a Soviet space dog who became the first living creature to orbit Earth, marking a pivotal moment in the early Space Race.
-
D.
Barkley
Barkley is a surname most notably associated with Alben W. Barkley, the 35th vice president of the United States under President Harry S. Truman.
-
E.
Shep
Shep is the station code used to identify Sheppard–Yonge station in the Toronto subway system.
- 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_69ad85b2fed48190948c8765e453d270 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb3af0cc81909e575828caeaeae0 |
completed | March 8, 2026, 6:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3680dd2c48190a06c5c320a06a71a |
completed | March 13, 2026, 1:27 a.m. |
Created at: March 8, 2026, 3:17 p.m.