Triple
T13395092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sai Masu Gida |
E319682
|
entity |
| Predicate | meaningNote |
P102770
|
FINISHED |
| Object | nickname in Hausa for Kano Pillars F.C. |
—
|
LITERAL 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: nickname in Hausa for Kano Pillars F.C. | Statement: [Sai Masu Gida, meaningNote, nickname in Hausa for Kano Pillars F.C.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meaningNote Context triple: [Sai Masu Gida, meaningNote, nickname in Hausa for Kano Pillars F.C.]
-
A.
meaningComponent
Indicates that one entity represents a semantic or conceptual component contributing to the overall meaning of another entity.
-
B.
meaningInContext
chosen
Indicates that one entity represents or conveys a particular meaning, interpretation, or sense within a specific context or situation.
-
C.
meaningViaAndrzej
Indicates that something’s meaning or interpretation is conveyed, mediated, or understood specifically through Andrzej.
-
D.
logicalMeaning
Indicates that one entity expresses, encodes, or conveys the logical content, implication, or formal meaning of another.
-
E.
commonMeaning
Indicates that multiple entities share the same or very similar meaning or semantic interpretation.
- F. None of above.
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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dba0d892d08190b1b192b93fe3d72d |
completed | April 12, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03189908190a784a2755f8d81e1 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:34 p.m.