Triple
T14998593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanga Region |
E374023
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Tanga |
E374023
|
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: Tanga | Statement: [Tanga Region, hasCapital, Tanga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tanga Context triple: [Tanga Region, hasCapital, Tanga]
-
A.
Manyanga
Manyanga was an important historical settlement in present-day Zimbabwe that served as the capital of the Rozvi Empire.
-
B.
Mambasa
Mambasa is a town and administrative center located in the forested Ituri region of northeastern Democratic Republic of the Congo.
-
C.
Tanga Region
chosen
Tanga Region is a coastal administrative region in northeastern Tanzania known for its port city of Tanga, Indian Ocean shoreline, and proximity to the Usambara Mountains.
-
D.
Takrur
Takrur was an early West African kingdom located in the Senegal River valley, known for its role in trans-Saharan trade and its early adoption of Islam.
-
E.
Malaweg
Malaweg is a Philippine language of northern Luzon, considered a variety or closely related member of the Ibanag language group.
- 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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded71a5618819083ae96a79735ef98 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe969c3ba88190899f06b185e94ccf |
completed | May 9, 2026, 2:06 a.m. |
Created at: April 10, 2026, 2:54 a.m.