Triple
T14612919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Batroun District |
E343004
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Kfifane
Kfifane is a village in northern Lebanon known for its Maronite Christian heritage and monastic presence.
|
E1111241
|
NE FINISHED |
How this triple was built (4 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: Kfifane | Statement: [Batroun District, containsSettlement, Kfifane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kfifane Context triple: [Batroun District, containsSettlement, Kfifane]
-
A.
Mfengu
The Mfengu are a Southern African ethnic group, historically refugees from earlier conflicts, who became known as allies of the British and Xhosa intermediaries during the 19th-century colonial frontier wars in the Eastern Cape.
-
B.
Kasangati
Kasangati is a town in central Uganda that serves as a growing commercial and residential hub within the Greater Kampala metropolitan area.
-
C.
Kwaluudhi
Kwaluudhi is a dialect of the Ovambo language spoken by a specific Ovambo subgroup in northern Namibia.
-
D.
Kumba
Kumba is a renowned steel roller coaster at Busch Gardens Tampa Bay, famous for its intense inversions and smooth, high-speed layout.
-
E.
Kumba
Kumba is a major town in southwestern Cameroon known as a commercial hub and cultural crossroads where languages like Cameroonian Pidgin English are widely used.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kfifane Triple: [Batroun District, containsSettlement, Kfifane]
Generated description
Kfifane is a village in northern Lebanon known for its Maronite Christian heritage and monastic presence.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kfifane Target entity description: Kfifane is a village in northern Lebanon known for its Maronite Christian heritage and monastic presence.
-
A.
Mfengu
The Mfengu are a Southern African ethnic group, historically refugees from earlier conflicts, who became known as allies of the British and Xhosa intermediaries during the 19th-century colonial frontier wars in the Eastern Cape.
-
B.
Kasangati
Kasangati is a town in central Uganda that serves as a growing commercial and residential hub within the Greater Kampala metropolitan area.
-
C.
Kwaluudhi
Kwaluudhi is a dialect of the Ovambo language spoken by a specific Ovambo subgroup in northern Namibia.
-
D.
Kumba
Kumba is a renowned steel roller coaster at Busch Gardens Tampa Bay, famous for its intense inversions and smooth, high-speed layout.
-
E.
Kumba
Kumba is a major town in southwestern Cameroon known as a commercial hub and cultural crossroads where languages like Cameroonian Pidgin English are widely used.
- F. None of above. chosen
Provenance (5 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb450e6588190a94488d8e71888c8 |
completed | April 14, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda92110e88190af47b713dd24520b |
completed | May 8, 2026, 9:13 a.m. |
| NEDg | Description generation | batch_69fdb35a57f08190a2d3fe426185bc31 |
completed | May 8, 2026, 9:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fdb400e08081908d0a782908ba5459 |
completed | May 8, 2026, 9:59 a.m. |
Created at: April 10, 2026, 1:25 a.m.