Triple
T13757199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basketball Wives |
E330505
|
entity |
| Predicate | featuresCastMember |
P7010
|
FINISHED |
| Object |
OG Chijindu
OG Chijindu is a Nigerian-American former professional athlete and reality television personality best known for her appearances on the VH1 series "Basketball Wives."
|
E1059214
|
NE FINISHED |
How this triple was built (4 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: OG Chijindu | Statement: [Basketball Wives, featuresCastMember, OG Chijindu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OG Chijindu Context triple: [Basketball Wives, featuresCastMember, OG Chijindu]
-
A.
Oghi
Oghi is a town in Pakistan's Khyber Pakhtunkhwa province, known as a local administrative and commercial center within the Hazara region.
-
B.
Jicha Gan
Jicha Gan is a regional variety of the Gan Chinese language spoken in parts of southern China.
-
C.
Ogi
Ogi was a former municipality on Sado Island in Niigata Prefecture, Japan, known for its coastal setting and later incorporation into the city of Sado.
-
D.
Kogo
Kogo is a settlement located in the Litoral region of Equatorial Guinea.
-
E.
Chìkàn Lóu
Chìkàn Lóu is the romanized name of Chihkan Tower, a historic Dutch-built fort and popular cultural landmark in Tainan, Taiwan.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: OG Chijindu Triple: [Basketball Wives, featuresCastMember, OG Chijindu]
Generated description
OG Chijindu is a Nigerian-American former professional athlete and reality television personality best known for her appearances on the VH1 series "Basketball Wives."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: OG Chijindu Target entity description: OG Chijindu is a Nigerian-American former professional athlete and reality television personality best known for her appearances on the VH1 series "Basketball Wives."
-
A.
Oghi
Oghi is a town in Pakistan's Khyber Pakhtunkhwa province, known as a local administrative and commercial center within the Hazara region.
-
B.
Jicha Gan
Jicha Gan is a regional variety of the Gan Chinese language spoken in parts of southern China.
-
C.
Ogi
Ogi was a former municipality on Sado Island in Niigata Prefecture, Japan, known for its coastal setting and later incorporation into the city of Sado.
-
D.
Kogo
Kogo is a settlement located in the Litoral region of Equatorial Guinea.
-
E.
Chìkàn Lóu
Chìkàn Lóu is the romanized name of Chihkan Tower, a historic Dutch-built fort and popular cultural landmark in Tainan, Taiwan.
- F. None of above. chosen
Provenance (5 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de022286b481908f8a801042743512 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7a85dfa6881908da90886db4aa1bb |
completed | May 3, 2026, 7:56 p.m. |
| NEDg | Description generation | batch_69f7a994cd688190a077a4854c5c71c9 |
completed | May 3, 2026, 8:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7aa32b8c8819088bbc9e478c21c06 |
completed | May 3, 2026, 8:04 p.m. |
Created at: April 9, 2026, 10:09 p.m.