Triple
T12916161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ciluba |
E308987
|
entity |
| Predicate | hasAlternativeSpelling |
P457
|
FINISHED |
| Object | Cilubà |
E308987
|
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: Cilubà | Statement: [Ciluba, hasAlternativeSpelling, Cilubà]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cilubà Context triple: [Ciluba, hasAlternativeSpelling, Cilubà]
-
A.
Sibulan
Sibulan is a coastal municipality in the Philippine province of Negros Oriental known as a gateway to Dumaguete City and for its local airport and seaport.
-
B.
Ciluba
chosen
Ciluba is a Bantu language spoken primarily in the Democratic Republic of the Congo, especially in the Kasai region.
-
C.
Cailungo
Cailungo is a locality within the municipality of Serravalle in the Republic of San Marino.
-
D.
Labuha
Labuha is a coastal town that serves as an important local center on the Indonesian island of Halmahera.
-
E.
Marawila
Marawila is a coastal town in Sri Lanka known for its beaches, fishing community, and tourism-oriented resorts.
- 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_69d7bdf92b588190acdf2a2291ac4590 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971a1e8088190af697629baecf59f |
completed | April 10, 2026, 9:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6a571a3e48190a32d362adc6eaee2 |
completed | May 3, 2026, 1:31 a.m. |
Created at: April 9, 2026, 5:41 p.m.