Triple
T6754040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sivas |
E154408
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object | Cabira |
E460802
|
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: Cabira | Statement: [Sivas, formerName, Cabira]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cabira Context triple: [Sivas, formerName, Cabira]
-
A.
Cabira
chosen
Cabira was an ancient city in the region of Pontus in Asia Minor, later known as Neocaesarea under Roman rule.
-
B.
Bignona
Bignona is a town in southern Senegal’s Casamance region, known as a local center of trade and cultural diversity.
-
C.
Langoué Baï
Langoué Baï is a renowned forest clearing in Gabon celebrated for its rich biodiversity and frequent gatherings of forest elephants and other wildlife.
-
D.
Sikasso
Sikasso is a major city in southern Mali known as an important agricultural and commercial center near the borders with Burkina Faso and Côte d'Ivoire.
-
E.
Tadjoura
Tadjoura is a historic coastal town in Djibouti on the Gulf of Tadjoura, known as one of the country’s oldest settlements and a traditional trading hub.
- 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_69c6880fd5808190be684854081e27dd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d1f32fa08190bb23dc24fef14c8d |
completed | March 27, 2026, 6:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70b1c4594819084716e21b16191e3 |
completed | March 27, 2026, 10:56 p.m. |
Created at: March 27, 2026, 2:11 p.m.