Triple
T18883680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baniyas |
E461897
|
entity |
| Predicate | hasNearbySettlement |
P4647
|
FINISHED |
| Object | Jableh |
—
|
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: Jableh | Statement: [Baniyas, hasNearbySettlement, Jableh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jableh Context triple: [Baniyas, hasNearbySettlement, Jableh]
-
A.
Jableh
chosen
Jableh is a coastal city in northwestern Syria on the Mediterranean Sea, known for its ancient history and archaeological sites, including a well-preserved Roman theater.
-
B.
Jibbali
Jibbali, also known as Shehri, is a Modern South Arabian language spoken in parts of Oman, closely related to Mehri and distinct from Arabic.
-
C.
Jabriya
Jabriya is a residential suburb in Kuwait known for its mix of apartment buildings, schools, and local shops within the Hawalli Governorate.
-
D.
Juban
Juban is a coastal municipality in the province of Sorsogon in the Bicol Region of the Philippines, known for its hot springs and scenic views of Mount Bulusan.
-
E.
Jazil
Jazil was an American Thoroughbred racehorse best known for winning the 2006 Belmont Stakes.
- 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.