Triple
T7274877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vannes |
E162998
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Limerick |
E71642
|
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: Limerick | Statement: [Vannes, twinTown, Limerick]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Limerick Context triple: [Vannes, twinTown, Limerick]
-
A.
Limerick
chosen
Limerick is a historic city in western Ireland known for its medieval architecture, riverside setting on the River Shannon, and rich cultural and literary heritage.
-
B.
Limerick City
Limerick City is a historic city in western Ireland, known for its medieval architecture, strategic location on the River Shannon, and role in key events of Irish history.
-
C.
Waterford
Waterford is a small incorporated city located in Stanislaus County in California’s Central Valley.
-
D.
Waterford
Waterford is a historic port city in southeast Ireland, renowned as the country’s oldest city and for its traditional crystal glassmaking.
-
E.
Waterford
Waterford is a small town and village in eastern New York State, known as the eastern terminus of the Erie Canal and its historic canal locks.
- 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_69c6885c5964819085b209701769877f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb0fd8788190aa21d4b2ad773926 |
completed | March 27, 2026, 8:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7db2c76fc81909632c7ee4e54f81c |
completed | March 28, 2026, 1:44 p.m. |
Created at: March 27, 2026, 2:58 p.m.