Triple
T6985234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kabylie |
E161944
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Tizi Ghenif |
E633340
|
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: Tizi Ghenif | Statement: [Kabylie, hasMajorCity, Tizi Ghenif]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tizi Ghenif Context triple: [Kabylie, hasMajorCity, Tizi Ghenif]
-
A.
Tizi Ouzou
Tizi Ouzou is a major city in northern Algeria known as a cultural and economic center of the Kabylie region and the Kabyle Berber people.
-
B.
Ifrane
Ifrane is a Moroccan mountain town in the Middle Atlas known for its alpine-style architecture, cool climate, and reputation as one of the country’s cleanest and most picturesque cities.
-
C.
Jbel Bou Naceur
Jbel Bou Naceur is a prominent mountain peak in Morocco known for its rugged terrain and scenic hiking routes.
-
D.
M'Ress
M'Ress is a feline-like Caitian Starfleet communications officer who appears as a recurring character in Star Trek: The Animated Series.
-
E.
Tizi Gheniff
chosen
Tizi Gheniff is a town and commune located in northern Algeria within the Kabylie region.
- 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_69c68855dc0481909b4c7e9e9ed273db |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db91fbc881908c26b7b991995062 |
completed | March 27, 2026, 7:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7754c817c8190a8b17a5e2c4f1b05 |
completed | March 28, 2026, 6:29 a.m. |
Created at: March 27, 2026, 2:31 p.m.