Triple
T11570058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mahe |
E274360
|
entity |
| Predicate | historicalName |
P65
|
FINISHED |
| Object | Mahé |
E166597
|
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: Mahé | Statement: [Mahe, historicalName, Mahé]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mahé Context triple: [Mahe, historicalName, Mahé]
-
A.
Mahé
Mahé is the largest and most populous island of Seychelles, home to the nation’s capital, Victoria, and its main economic and cultural center.
-
B.
Mahé
chosen
Mahé is a former French colonial settlement on the Malabar Coast of India, now a small coastal town and district enclave of the Union Territory of Puducherry.
-
C.
Praslin
Praslin is the second-largest island of Seychelles, renowned for its white-sand beaches, lush tropical forests, and the UNESCO-listed Vallée de Mai nature reserve.
-
D.
Nosy Be
Nosy Be is a popular resort island off the northwest coast of Madagascar, known for its beaches, marine life, and volcanic lakes.
-
E.
Mahe
Mahe is a small coastal town on the Arabian Sea that forms a geographically separated district of the Union Territory of Puducherry in India.
- 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_69d6aae5ac3c81908d2b0a3a665665b2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d88dd543a48190b834abd8e8ae7b65 |
completed | April 10, 2026, 5:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6e8dec908819080d97cd33be55b3f |
completed | April 21, 2026, 3:02 a.m. |
Created at: April 8, 2026, 9:37 p.m.