Triple
T14536393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince of Zamunda |
E341053
|
entity |
| Predicate | country |
P26
|
FINISHED |
| Object | Zamunda |
E341023
|
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: Zamunda | Statement: [Prince of Zamunda, country, Zamunda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zamunda Context triple: [Prince of Zamunda, country, Zamunda]
-
A.
Zamunda
chosen
Zamunda is the fictional wealthy African kingdom that serves as the primary setting in the comedy film "Coming to America."
-
B.
Hidari Zingaro
Hidari Zingaro is a contemporary art gallery in Tokyo associated with artist Takashi Murakami’s Kaikai Kiki collective, known for showcasing cutting-edge and pop-influenced works.
-
C.
Mnajdra
Mnajdra is an ancient megalithic temple complex on Malta’s southern coast, renowned for its prehistoric architecture and astronomical alignments.
-
D.
Gilga
Gilga is a production company known for its work on the television series "Swarm."
-
E.
Bailundo
Bailundo is a town and municipality in central Angola, historically significant as the seat of the Ovimbundu kingdom of Bailundo.
- 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb1b9d39881908c7a3a5b17d432af |
completed | April 14, 2026, 9:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fde16666b8819090fb33c71515ab0a |
completed | May 8, 2026, 1:13 p.m. |
Created at: April 10, 2026, 1:22 a.m.