Triple
T5916794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Marvelous Land of Oz |
E131599
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Mombi |
E161151
|
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: Mombi | Statement: [The Marvelous Land of Oz, mainCharacter, Mombi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mombi Context triple: [The Marvelous Land of Oz, mainCharacter, Mombi]
-
A.
Mombi
chosen
Mombi is a wicked witch from L. Frank Baum’s Oz series, best known for usurping and enchanting Princess Ozma to conceal her true identity.
-
B.
Hamutal
Hamutal was a queen of Judah, known as the mother of the last king of Judah, Zedekiah, during the final years before the Babylonian exile.
-
C.
Mandodari
Mandodari is a revered queen in the Hindu epic Ramayana, known as the wise and virtuous wife of the demon king Ravana.
-
D.
Zilu
Zilu was one of Confucius’s most prominent disciples, known for his bravery, straightforwardness, and frequent appearance in the Analects as a key interlocutor.
-
E.
Malongo
Malongo is a major offshore oil field and production hub located off the coast of Cabinda in Angola.
- 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_69c0085a1ed08190a7e9a8b6323fd680 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c037bcea9c8190a34dc03857e3b80b |
completed | March 22, 2026, 6:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c02c24cc8190a98d24f7445f59b7 |
completed | March 23, 2026, 4:23 a.m. |
Created at: March 22, 2026, 3:59 p.m.