Triple
T14828912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sai River |
E348645
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object | Sai Nadi |
E69557
|
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: Sai Nadi | Statement: [Sai River, hasNameInLanguage, Sai Nadi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sai Nadi Context triple: [Sai River, hasNameInLanguage, Sai Nadi]
-
A.
Rao River
The Rao River is a significant river in Jiangxi Province, China, that serves as one of the main tributaries supplying water to Poyang Lake.
-
B.
Amaravati River
The Amaravati River is a significant river in southern India that flows through the state of Tamil Nadu, supporting agriculture and local ecosystems before joining the Kaveri.
-
C.
Siva River
The Siva River is a tributary waterway in Russia that feeds into the Kama River within the Volga basin.
-
D.
Sarayu
chosen
Sarayu is a significant river in northern India, traditionally associated with the ancient city of Ayodhya and revered in Hindu mythology.
-
E.
Sadanandavathi
Sadanandavathi was the first wife of Indian actor and politician M. G. Ramachandran.
- 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_69d822eb8f588190bf53445e730a934f |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded0737d4c8190a49bf6b013da208c |
completed | April 14, 2026, 11:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff133571008190b7e7867208095b90 |
completed | May 9, 2026, 10:57 a.m. |
Created at: April 10, 2026, 1:51 a.m.