Triple
T2128751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siyani Chambers |
E46485
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Siyani |
E46485
|
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: Siyani | Statement: [Siyani Chambers, givenName, Siyani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siyani Context triple: [Siyani Chambers, givenName, Siyani]
-
A.
Siyani
chosen
Siyani is a given name most notably associated with Siyani Chambers, an American basketball player known for his collegiate career at Harvard University.
-
B.
Bongi
Bongi is a neighborhood located in the city of Recife, in northeastern Brazil.
-
C.
Soshanguve
Soshanguve is a large township in the northern part of the Gauteng province of South Africa, known for its diverse population and proximity to Pretoria.
-
D.
Sanglechi
Sanglechi is a lesser-known Eastern Iranian language spoken in parts of northeastern Afghanistan and adjacent regions.
-
E.
Lilangeni
The lilangeni is the official monetary unit of Eswatini, subdivided into 100 cents and commonly used alongside the South African rand.
- 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_69a88a1626548190ae59a5028c3baa8e |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbb7659f48190871cb27faf47e18a |
completed | March 7, 2026, 5:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae51a36398819081df18cc18bc3456 |
completed | March 9, 2026, 4:50 a.m. |
Created at: March 4, 2026, 7:44 p.m.