Triple
T15792839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ganja International Airport |
E382900
|
entity |
| Predicate | cityServed |
P82
|
FINISHED |
| Object | Ganja |
E80938
|
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: Ganja | Statement: [Ganja International Airport, cityServed, Ganja]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ganja Context triple: [Ganja International Airport, cityServed, Ganja]
-
A.
Ganja
chosen
Ganja is one of Azerbaijan’s largest and oldest cities, known as a historic cultural and economic center in the South Caucasus.
-
B.
União do Vegetal
União do Vegetal is a Brazilian syncretic religious organization that uses the psychoactive tea ayahuasca as a sacrament in its spiritual ceremonies.
-
C.
Cannabis
Cannabis is a genus of flowering plants best known for producing psychoactive and medicinal compounds such as THC and CBD, widely used for recreational, therapeutic, and industrial (hemp) purposes.
-
D.
Sahl Hasheesh
Sahl Hasheesh is a modern Red Sea coastal resort town in Egypt known for its luxury hotels, beaches, and diving and snorkeling sites.
-
E.
Sabu
Sabu is a pioneering hardcore professional wrestler best known for his extreme, high-risk style and influential run in ECW.
- 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4da381c819086195e3d20591abf |
completed | April 16, 2026, 10:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb036ee7c8190a8b8da79589ebec0 |
completed | May 9, 2026, 10:07 p.m. |
Created at: April 10, 2026, 4:48 a.m.