Triple
T3355012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wolof Empire |
E70583
|
entity |
| Predicate | vassalState |
P47437
|
FINISHED |
| Object | Sine |
E350753
|
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: Sine | Statement: [Wolof Empire, vassalState, Sine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sine Context triple: [Wolof Empire, vassalState, Sine]
-
A.
Sine
chosen
Sine was a precolonial Serer kingdom in what is now Senegal, known for its rich Serer culture, religious traditions, and resistance to Islamic and later French expansion.
-
B.
Sines
Sines is a coastal town in Portugal known as the birthplace of the famed explorer Vasco da Gama.
-
C.
Trigon
Trigon is a powerful demonic supervillain in the Teen Titans universe, best known as Raven’s tyrannical father and a major cosmic threat.
-
D.
Zrsinus
Zrsinus is the Latinized name of Zacharias Ursinus, a 16th-century German Reformed theologian best known as a principal author of the Heidelberg Catechism.
-
E.
Sinn
Sinn is a river in northern Bavaria, Germany, that flows through the Lower Franconia 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_69ad85a4ef7c8190a29e2bbd6fa454e4 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb2419a808190a54fc03eeec6e42d |
completed | March 8, 2026, 5:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3342cf54081909d47876ff4ad4e81 |
completed | March 12, 2026, 9:46 p.m. |
Created at: March 8, 2026, 3:13 p.m.