Triple
T18883681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baniyas |
E461897
|
entity |
| Predicate | hasNearbySettlement |
P4647
|
FINISHED |
| Object | Safita |
—
|
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: Safita | Statement: [Baniyas, hasNearbySettlement, Safita]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Safita Context triple: [Baniyas, hasNearbySettlement, Safita]
-
A.
Safita
chosen
Safita is a historic hilltop town in western Syria known for its prominent Crusader-era fortress, the White Tower.
-
B.
Salhiya
Salhiya is a district within Kuwait's Capital Governorate, known primarily as a commercial and residential area in Kuwait City.
-
C.
Béja
Béja is a historic city in northwestern Tunisia known for its agricultural importance and Roman-era heritage.
-
D.
Asilah
Asilah is a historic fortified coastal town in northern Morocco known for its whitewashed medina, Atlantic beaches, and annual cultural and arts festivals.
-
E.
Ghadamisi
Ghadamisi is an alternative name for the Ghadamès Berber language spoken in and around the oasis town of Ghadamès in western Libya.
- 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_69d8dcfc3430819095ee6fc0eb4c06a5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c3d3dcec8190a468162c6a4482f6 |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 10, 2026, 11:57 a.m.