Triple
T16565807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Breamish |
E402456
|
entity |
| Predicate | flowsNear |
P350
|
FINISHED |
| Object | Ingram |
E973379
|
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: Ingram | Statement: [River Breamish, flowsNear, Ingram]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ingram Context triple: [River Breamish, flowsNear, Ingram]
-
A.
Ingram
Ingram is a surname of English origin borne by various notable individuals across fields such as music, sports, and academia.
-
B.
Ingram
chosen
Ingram is a small city in Kerr County, Texas, known for its scenic Hill Country setting along the Guadalupe River.
-
C.
Harcout
Harcourt is a small rural town in central Victoria, Australia, known historically for its apple orchards and granite quarries.
-
D.
Blackwell
Blackwell is a prominent academic publishing company known for producing scholarly books and journals across a wide range of disciplines.
-
E.
Blackwell
Blackwell is a surname of English origin borne by numerous notable individuals across fields such as music, politics, and academia.
- 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_69d8838648088190acf97ef11fc3f61b |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e357711ea481909468147375051bb4 |
completed | April 18, 2026, 10:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006ee1c1d0819096367344e48bd8d0 |
completed | May 10, 2026, 11:41 a.m. |
Created at: April 10, 2026, 5:15 a.m.