Triple
T5909261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Nigeria |
E131419
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object | Jos |
E59896
|
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: Jos | Statement: [Central Nigeria, majorCity, Jos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jos Context triple: [Central Nigeria, majorCity, Jos]
-
A.
Jos
chosen
Jos is a major city in central Nigeria known for its relatively temperate climate, tin mining history, and role as an administrative and commercial center.
-
B.
Jo
Jo is a given name used across various cultures, often as a short form of names like Joseph, Joanna, or Jonathan.
-
C.
Jud
Jud is a masculine given name, often used as a short form of names like Judson or Judah.
-
D.
Josh
Josh is a fictional political operative best known as the sharp-witted Deputy White House Chief of Staff on the television series "The West Wing."
-
E.
Josh
Josh is a character in the horror film "Midsommar," portrayed as one of the American graduate students who travel to a remote Swedish commune for a midsummer festival that turns increasingly disturbing.
- 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_69c008593a44819081a07ae0efe6c574 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03775590481909a797b166fbe108c |
completed | March 22, 2026, 6:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0b16f568081908839cd2403b7534c |
completed | March 23, 2026, 3:20 a.m. |
Created at: March 22, 2026, 3:59 p.m.