Triple
T11739236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Athens metropolitan area |
E279108
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Galatsi |
E291384
|
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: Galatsi | Statement: [Athens metropolitan area, hasPart, Galatsi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Galatsi Context triple: [Athens metropolitan area, hasPart, Galatsi]
-
A.
Galatsi
chosen
Galatsi is a densely populated suburban municipality of Athens, Greece, known for its residential character and proximity to the city center.
-
B.
Galatia
Galatia was an ancient region in central Asia Minor, historically inhabited by Celtic tribes and later incorporated into the Roman Empire as a province.
-
C.
Galaosiyo
Galaosiyo is a town in Uzbekistan that serves as a local urban center within the historic Bukhara Region.
-
D.
Greccio
Greccio is a small medieval hill town in central Italy renowned as the place where Saint Francis of Assisi created the first live Nativity scene.
-
E.
Evrytania
Evrytania is a mountainous regional unit in western Central Greece known for its rugged landscapes, forests, and traditional villages.
- 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_69d6aaffec6881908bead509e8621742 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4ef1c4881909ad36dc27b1fe193 |
completed | April 10, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f019c339cc81909967ecfa234e4ab8 |
completed | April 28, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:41 p.m.