Triple
T12424281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Suir |
E296857
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Waterford |
E285705
|
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: Waterford | Statement: [River Suir, flowsThrough, Waterford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waterford Context triple: [River Suir, flowsThrough, Waterford]
-
A.
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.
-
B.
Waterford
Waterford is a small incorporated city located in Stanislaus County in California’s Central Valley.
-
C.
Waterford
chosen
Waterford is a historic port city in southeast Ireland, renowned as the country’s oldest city and for its traditional crystal glassmaking.
-
D.
Wexford
Wexford is a historic coastal town in County Wexford, Ireland, known for its medieval heritage and role in events such as the 1649 siege during the Cromwellian conquest.
-
E.
Tuam
Tuam is a historic market town in western Ireland known for its ecclesiastical heritage and role as a regional center in County Galway.
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d7b6bd08190b30beba393a5b1e7 |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f726570a2481909f417be6e38d283a |
completed | May 3, 2026, 10:41 a.m. |
Created at: April 8, 2026, 9:55 p.m.