Triple
T34619756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of the Court of Appeal of Nigeria |
E888968
|
entity |
| Predicate | officeHousedIn |
P29918
|
FINISHED |
| Object | Court of Appeal Headquarters, Abuja |
—
|
NE NERFINISHED |
How this triple was built (1 step)
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: Court of Appeal Headquarters, Abuja | Statement: [President of the Court of Appeal of Nigeria, officeHousedIn, Court of Appeal Headquarters, Abuja]
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_69f349d584e08190b40b9f6281ad50c4 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f72222b6e88190be30f6e046729ba6 |
completed | May 3, 2026, 10:23 a.m. |
Created at: May 1, 2026, 2:03 a.m.