Triple
T2887231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cross River State |
E59533
|
entity |
| Predicate | hasLocalGovernmentArea |
P8215
|
FINISHED |
| Object | Yala |
E306887
|
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: Yala | Statement: [Cross River State, hasLocalGovernmentArea, Yala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yala Context triple: [Cross River State, hasLocalGovernmentArea, Yala]
-
A.
Yala
Yala is a major city in Thailand’s deep south, known as an administrative, commercial, and cultural center near the Malaysian border.
-
B.
Yala
chosen
Yala is a language spoken by the Yala people of Cross River State in southeastern Nigeria.
-
C.
Gela Sule
Gela Sule is a variant name for Nggela Sule, a locality associated with the Nggela (Florida) Islands in the Solomon Islands.
-
D.
Tantu
Tantu is a Kannada novel by acclaimed Indian writer S. L. Bhyrappa, known for its exploration of complex social and philosophical themes.
-
E.
Tarhuna
Tarhuna is a town in northwestern Libya, southeast of Tripoli, known for its strategic role and tribal influence during the Libyan civil conflicts.
- 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_69ab4ac739188190a112f42a5a69c951 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abe047aa7c8190a0ed570c13f3a1a2 |
completed | March 7, 2026, 8:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b055f2d72c8190b81b2b0b3093ae57 |
completed | March 10, 2026, 5:33 p.m. |
Created at: March 6, 2026, 10:03 p.m.