Triple
T11531851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Panther universe |
E273440
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Nakia |
E229436
|
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: Nakia | Statement: [Black Panther universe, featuresCharacter, Nakia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nakia Context triple: [Black Panther universe, featuresCharacter, Nakia]
-
A.
Nakia
chosen
Nakia is a skilled Wakandan spy and warrior in the Marvel Cinematic Universe, known for her courage, compassion, and close ties to T’Challa and Wakanda.
-
B.
Nakia
Nakia is a 1970s American television drama series centered on a Native American deputy sheriff navigating crime and cultural tensions in a small New Mexico town.
-
C.
Harmony Parker
Harmony Parker is the imaginative young girl who discovers a magical 50p coin that grants wishes in the children's book and TV series "The Queen's Nose."
-
D.
Nakia Bahadir
Nakia Bahadir is a close friend and ally of Kamala Khan in Marvel Comics, known for her strong principles, activism, and support of Ms. Marvel.
-
E.
Dameisha
Dameisha is a popular coastal area in Shenzhen, China, best known for its long sandy beach, seaside resorts, and recreational attractions.
- 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_69d6aae3fbec8190a14632a5df2538b6 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8839878948190b170e64629d6f2db |
completed | April 10, 2026, 4:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e68577f5ec8190a46687119d288a36 |
completed | April 20, 2026, 7:58 p.m. |
Created at: April 8, 2026, 9:37 p.m.