Triple
T4983959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drâa-Tafilalet |
E111955
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Ouarzazate |
E504363
|
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: Ouarzazate | Statement: [Drâa-Tafilalet, containsCity, Ouarzazate]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ouarzazate Context triple: [Drâa-Tafilalet, containsCity, Ouarzazate]
-
A.
Ouarzazate
chosen
Ouarzazate is a city in south-central Morocco known as a gateway to the Sahara Desert and a major hub for film production and desert tourism.
-
B.
Tiznit
Tiznit is a historic town in southern Morocco known for its traditional silver jewelry craftsmanship and fortified old medina.
-
C.
Guelmim
Guelmim is a city in southern Morocco known as a gateway to the Sahara and a regional center for Saharan trade and culture.
-
D.
Oujda
Oujda is a major city in northeastern Morocco near the Algerian border, known as an important commercial and cultural center of the region.
-
E.
Sefrou
Sefrou is a historic town in northern Morocco known for its traditional medina, cherry festival, and location near the Middle Atlas mountains.
- 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_69bd441adc208190b70a033a0741d01e |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7255d7b4819098b537df5b1a4c3c |
completed | March 20, 2026, 4:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bfc83116408190b558cb3eb5dc678f |
completed | March 22, 2026, 10:45 a.m. |
Created at: March 20, 2026, 1:33 p.m.