Triple
T12543078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lori Province |
E299890
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Alaverdi |
E446332
|
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: Alaverdi | Statement: [Lori Province, hasTown, Alaverdi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alaverdi Context triple: [Lori Province, hasTown, Alaverdi]
-
A.
Alaverdi
chosen
Alaverdi is a small industrial town in northern Armenia known for its historic copper mining industry and its location in the Debed River gorge near several UNESCO-listed monasteries.
-
B.
Ayvansaray
Ayvansaray is a historic neighborhood on the Golden Horn in Istanbul, known for its old city walls, traditional wooden houses, and rich Byzantine and Ottoman heritage.
-
C.
Manyas
Manyas is a town and district in northwestern Turkey known for its proximity to Lake Manyas and its rich birdlife.
-
D.
Yusufeli
Yusufeli is a small mountainous town and district in Artvin Province in northeastern Turkey, known for its rugged landscape and proximity to the Çoruh River.
-
E.
Gülnar
Gülnar is a rural district and town in southern Turkey known for its mountainous terrain and agricultural economy within Mersin Province.
- 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_69d6ada707008190aaec1238117c9379 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9547d6df4819080db8415d386ed38 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6557e6d4c81909ed54a039e92a160 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 9:57 p.m.