Triple
T12388268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kombe |
E295925
|
entity |
| Predicate | alternateName |
P39
|
FINISHED |
| Object | Kômbe |
E295925
|
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: Kômbe | Statement: [Kombe, alternateName, Kômbe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kômbe Context triple: [Kombe, alternateName, Kômbe]
-
A.
Kombe
chosen
Kombe is a Bantu language spoken by the Kombe people of coastal Equatorial Guinea and nearby regions, closely related to other Ndowe-area languages.
-
B.
Cembo
Cembo is a residential and commercial barangay in Makati City, Philippines, known for its dense urban community and proximity to major business districts.
-
C.
Koman
Koman is a small language family of northeastern Africa whose member languages are spoken primarily in border regions of Ethiopia and Sudan.
-
D.
Kasama
Kasama is a major town in northern Zambia that serves as the administrative and commercial center of the Northern Province.
-
E.
Mekambo
Mekambo is a small town in northeastern Gabon that serves as a local administrative and service center within the forested Ogooué-Ivindo region.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fcf6aa8819080c9a2407a72db2e |
completed | April 10, 2026, 6:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6347816408190904ea71d2a72398f |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:54 p.m.