Triple
T17221478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pikine Department |
E417993
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Pikine |
E1258759
|
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: Pikine | Statement: [Pikine Department, contains, Pikine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pikine Context triple: [Pikine Department, contains, Pikine]
-
A.
Pikine
chosen
Pikine is a major suburban city in the Dakar Region of Senegal, known for its dense population and role as part of the greater Dakar metropolitan area.
-
B.
Ambouli
Ambouli is a district of Djibouti City that hosts the country’s main international airport and related urban infrastructure.
-
C.
Biassou
Biassou was a prominent early leader of the Haitian Revolution, known for his role in organizing and directing the initial slave uprisings against French colonial rule.
-
D.
Koudougou
Koudougou is a major city in central Burkina Faso known as an important commercial and transportation hub.
-
E.
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.
- 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_69d886d779488190b131369541c04e7d |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42dde78f881908b03105fa0298ae2 |
completed | April 19, 2026, 1:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01793cfaf08190bff9a6efe01d5bea |
completed | May 11, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:38 a.m.