Triple
T11824616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rikki-Tikki-Tavi |
E281226
|
entity |
| Predicate | kills |
P19780
|
FINISHED |
| Object | Nagaina |
E949710
|
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: Nagaina | Statement: [Rikki-Tikki-Tavi, kills, Nagaina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nagaina Context triple: [Rikki-Tikki-Tavi, kills, Nagaina]
-
A.
Nagaina
chosen
Nagaina is the deadly female cobra antagonist in Rudyard Kipling’s “Rikki-Tikki-Tavi,” known for plotting against the human family and their mongoose protector.
-
B.
Kama River
The Kama River is a major waterway in western Russia that serves as one of the largest and most significant tributaries of the Volga River.
-
C.
Adda River
The Adda River is a major river in northern Italy that flows through the Lombardy region, including forming part of Lake Como, before joining the Po River.
-
D.
Jhilimili Nala
Jhilimili Nala is a minor riverine stream in India that serves as one of the tributaries feeding into the Hasdeo River system.
-
E.
Muchukunda River
Muchukunda River is the historical name of the Musi River, a significant tributary of the Krishna River flowing through Hyderabad in the Indian state of Telangana.
- 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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5eb299481909de3c0e85628fbe4 |
completed | April 10, 2026, 7:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f2812007dc81908e56fd47b2a94836 |
completed | April 29, 2026, 10:07 p.m. |
Created at: April 8, 2026, 9:43 p.m.