Triple
T15251249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Master of the Order of Aviz |
E364522
|
entity |
| Predicate | basedIn |
P40
|
FINISHED |
| Object | Aviz |
E413181
|
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: Aviz | Statement: [Master of the Order of Aviz, basedIn, Aviz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aviz Context triple: [Master of the Order of Aviz, basedIn, Aviz]
-
A.
Aviz
chosen
Aviz is a historic town in Portugal known for giving its name to the Portuguese royal House of Aviz.
-
B.
Azaire
Azaire is a French surname notably associated with the character Isabelle Azaire from Sebastian Faulks’s novel "Birdsong."
-
C.
Ozar
Ozar is a town in the Nashik district of Maharashtra, India, known for its proximity to Nashik city and its role as a regional industrial and aviation hub.
-
D.
Zanaki
Zanaki are a small Bantu-speaking ethnic group in northern Tanzania, historically known as the people of King Nyerere, father of Tanzania’s first president Julius Nyerere.
-
E.
Azazga
Azazga is a significant town in northern Algeria’s Kabylie region, known as a local cultural and economic center for the Amazigh (Berber) population.
- 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_69d85a0dde7481908fc64d1e82d5d20d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007f728648190b2c86e4528542b65 |
completed | April 15, 2026, 9:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fee5f390bc8190bc0180c118e1523c |
completed | May 9, 2026, 7:44 a.m. |
Created at: April 10, 2026, 3:13 a.m.