Triple
T19559703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hida River |
E489412
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Gero |
—
|
NE NERFINISHED |
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: Gero | Statement: [Hida River, flowsThrough, Gero]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gero Context triple: [Hida River, flowsThrough, Gero]
-
A.
Gero
chosen
Gero is a Japanese hot spring resort city in Gifu Prefecture, renowned for its historic onsen baths and scenic mountain surroundings.
-
B.
Gero the Great
Gero the Great was a 10th-century Saxon margrave of the Eastern March in the Holy Roman Empire, known for his military campaigns and expansion of German control over Slavic territories.
-
C.
Gery
Gery is a spelling variant of the given name Gerry, typically used as a personal name.
-
D.
Gerenia
Gerenia is an ancient town in Messenia, Greece, best known in Greek mythology as the homeland of the wise hero Nestor.
-
E.
Geras
Geras is the Greek personification of old age, often depicted as a withered, decrepit figure and associated with the inevitable decline that comes with time.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63f731ae48190ade295c15db7f8ed |
completed | April 20, 2026, 3 p.m. |
Created at: April 10, 2026, 1:42 p.m.