Triple
T22824128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tana |
E565305
|
entity |
| Predicate | nicknameFor |
P2937
|
FINISHED |
| Object | Antananarivo |
—
|
NE NERFINISHED |
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: Antananarivo | Statement: [Tana, nicknameFor, Antananarivo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Antananarivo Context triple: [Tana, nicknameFor, Antananarivo]
-
A.
Antananarivo
chosen
Antananarivo is the capital and largest city of Madagascar, serving as its political, economic, and cultural center.
-
B.
Antsirabe
Antsirabe is a highland city in central Madagascar known for its cool climate, thermal springs, and colonial-era architecture.
-
C.
Bidassoa
Bidassoa is a river in the western Pyrenees that forms part of the border between France and Spain before flowing into the Bay of Biscay.
-
D.
Ambato
Ambato is a major city in the central Andean region of Ecuador, known for its agricultural production, textile industry, and annual Festival of Fruits and Flowers.
-
E.
Mamoudzou
Mamoudzou is the largest city and main administrative and economic center of the French overseas department of Mayotte in the Indian Ocean.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2458426188190b58b8ab4844fe420 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17dd34a248190881f2bccdd9aedce |
completed | April 29, 2026, 3:41 a.m. |
Created at: April 17, 2026, 3:34 p.m.