Triple
T6704426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lough Derg |
E152962
|
entity |
| Predicate | nearSettlement |
P3883
|
FINISHED |
| Object | Killaloe |
E150519
|
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: Killaloe | Statement: [Lough Derg, nearSettlement, Killaloe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Killaloe Context triple: [Lough Derg, nearSettlement, Killaloe]
-
A.
Killaloe
chosen
Killaloe is a historic town in County Clare, Ireland, known for its picturesque setting on the River Shannon and its association with High King Brian Boru.
-
B.
Kallady
Kallady is a coastal village in eastern Sri Lanka known for its beaches, fishing community, and proximity to the town of Batticaloa.
-
C.
Kiloran
Kiloran is a small coastal settlement on the Scottish island of Colonsay, known for its scenic bay and sandy beach.
-
D.
Killala
Killala is a small coastal town in County Mayo, Ireland, historically noted as the site of a French landing during the 1798 Irish Rebellion.
-
E.
Kaiten
Kaiten was a Japanese warship that took part in the late-19th-century Boshin War naval engagements, including the Battle of Hakodate.
- 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_69c68807adbc8190b8632df42b39eda0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d0e919748190953d893eb61724e7 |
completed | March 27, 2026, 6:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70085ed8c81909cb407ab183ebbe5 |
completed | March 27, 2026, 10:11 p.m. |
Created at: March 27, 2026, 2:06 p.m.