Triple
T19805510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fier region |
E475800
|
entity |
| Predicate | historicalRegion |
P915
|
FINISHED |
| Object | Myzeqe |
—
|
NE NERFINISHED |
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: Myzeqe | Statement: [Fier region, historicalRegion, Myzeqe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Myzeqe Context triple: [Fier region, historicalRegion, Myzeqe]
-
A.
Myzeqe
chosen
Myzeqe is a fertile lowland area in western Albania, known historically as an important agricultural heartland and cultural subregion of the Tosk-speaking population.
-
B.
Anjezë
Anjezë is the birth name of Mother Teresa, the Catholic nun and missionary renowned for her humanitarian work among the poor in Kolkata, India.
-
C.
Cezmi
Cezmi is a historical novel by Ottoman writer Namık Kemal, often regarded as one of the early examples of Turkish nationalist literature.
-
D.
Molazzana
Molazzana is a small municipality in Tuscany, central Italy, known for its scenic location in the Garfagnana area of the Apennine mountains.
-
E.
Njimi
Njimi was an important medieval city that served as the early capital of the Kanem-Bornu Empire in Central Africa.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65428081c8190b394c442f4c2a9a6 |
completed | April 20, 2026, 4:28 p.m. |
Created at: April 10, 2026, 1:49 p.m.