Triple
T15585102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liaoyang |
E374598
|
entity |
| Predicate | locatedOnRiver |
P165
|
FINISHED |
| Object | Taizi River |
E1160384
|
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: Taizi River | Statement: [Liaoyang, locatedOnRiver, Taizi River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taizi River Context triple: [Liaoyang, locatedOnRiver, Taizi River]
-
A.
Taizi River
chosen
The Taizi River is a major river in northeastern China that flows through Liaoning Province, including the city of Benxi, and serves as an important regional waterway.
-
B.
Luhan River
The Luhan River is a waterway in eastern Ukraine that flows through the Luhansk region, including the town of Slavyanoserbsk.
-
C.
Luo River
The Luo River is a significant tributary in central China that flows through Henan and Shaanxi provinces before joining the Yellow River.
-
D.
Wu River
The Wu River is a significant river in southwestern China known for flowing through deep gorges and contributing substantially to the Yangtze River system.
-
E.
Jialing River
The Jialing River is a significant river in southwestern China that flows through Sichuan and Chongqing, contributing heavily to the region’s water resources, transportation, and ecology.
- 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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e47971481909e986dd999354628 |
completed | April 16, 2026, 2:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff875bb0808190a6a4e3b47b524689 |
completed | May 9, 2026, 7:13 p.m. |
Created at: April 10, 2026, 4:11 a.m.