Triple
T4876609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katchal |
E109219
|
entity |
| Predicate | hasDialectContinuumWith |
P18451
|
FINISHED |
| Object | Camorta |
E394592
|
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: Camorta | Statement: [Katchal, hasDialectContinuumWith, Camorta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Camorta Context triple: [Katchal, hasDialectContinuumWith, Camorta]
-
A.
Camorta
chosen
Camorta is an island in India’s Nicobar archipelago in the eastern Indian Ocean, known for its indigenous Nicobarese communities and strategic location.
-
B.
Amarah
Amarah is a city in southeastern Iraq situated along the Tigris River and serving as the capital of Maysan Governorate.
-
C.
Grimus
Grimus is Salman Rushdie’s debut novel, a genre-blending work of science fiction and fantasy that explores themes of identity, immortality, and exile.
-
D.
Auxerrois
Auxerrois refers to a person from the city of Auxerre in France, and by extension can also denote things associated with that city.
-
E.
Auxerrois
Auxerrois is a French red wine grape variety more commonly known as Malbec, widely used in robust, deeply colored wines.
- 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_69bd440e9d64819083e82cf33b4d9570 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6dbbc734819083b28a022e5690d6 |
completed | March 20, 2026, 3:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be6fb5da2c8190aeec7d6d11b12b11 |
completed | March 21, 2026, 10:15 a.m. |
Created at: March 20, 2026, 1:27 p.m.