Triple
T9093197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gifhorn |
E217943
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object | Ise |
E173121
|
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: Ise | Statement: [Gifhorn, hasRiver, Ise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ise Context triple: [Gifhorn, hasRiver, Ise]
-
A.
Ise
Ise is a Japanese city in Mie Prefecture best known as the site of Ise Grand Shrine, the most sacred Shinto shrine dedicated to the sun goddess Amaterasu.
-
B.
Ise
chosen
The Ise is a river in Lower Saxony, Germany, known as a tributary of the Aller and part of the Weser river system.
-
C.
Ise
Ise was a Japanese Imperial Navy battleship later converted into a hybrid battleship–aircraft carrier during World War II.
-
D.
Yamatogawa
Yamatogawa is the romanized name of the Yamato River, a significant waterway in the Kansai region of Japan.
-
E.
Nagaokakyo
Nagaokakyo is a suburban city in Japan known for its bamboo groves, historical temples, and convenient location between Kyoto and Osaka.
- 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_69ca83d8ab5881909d8fddae363b32b1 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc96b347d4819085b33d0e20834f47 |
completed | April 1, 2026, 3:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d01803b0288190a86b544892d4b6ed |
completed | April 3, 2026, 7:41 p.m. |
Created at: March 30, 2026, 7:14 p.m.