Triple
T8529216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tipaza Province |
E201899
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Tipaza |
E671843
|
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: Tipaza | Statement: [Tipaza Province, hasCapital, Tipaza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tipaza Context triple: [Tipaza Province, hasCapital, Tipaza]
-
A.
Tipaza
chosen
Tipaza is a coastal town in northern Algeria known for its significant Roman archaeological ruins and scenic Mediterranean setting.
-
B.
Tapaz
Tapaz is a landlocked agricultural municipality in the province of Capiz on Panay Island in the Philippines, known for its rural landscapes and river valleys.
-
C.
Tupiza
Tupiza is a small historic town in southern Bolivia known for its dramatic red-rock canyons and as a gateway to Andean landscapes and mining regions.
-
D.
Palatak
Palatak is a notable literary work by Bengali writer and playwright Jyotirindranath Tagore.
-
E.
Pitalito
Pitalito is a major town and coffee-producing hub in southern Colombia, known as one of the country’s most important centers for high-quality coffee.
- 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_69ca83228b24819085d22e7dc99f5d94 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe67409f08190b20d13d26e9a362c |
completed | March 31, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce6d5e5b58819095c1c915dfe27b52 |
completed | April 2, 2026, 1:21 p.m. |
Created at: March 30, 2026, 6:17 p.m.