Triple
T10468781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jafar |
E246870
|
entity |
| Predicate | enemyOf |
P437
|
FINISHED |
| Object | Genie |
E347351
|
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: Genie | Statement: [Jafar, enemyOf, Genie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Genie Context triple: [Jafar, enemyOf, Genie]
-
A.
Genie
chosen
Genie is a powerful, wisecracking magical being from Disney's animated film "Aladdin," best known for granting wishes and his energetic, comedic personality.
-
B.
Lili
Lili is a 1953 musical fantasy film starring Leslie Caron as a naive orphan who joins a carnival and forms a touching bond with a puppeteer.
-
C.
Lili
Lili is the official mascot character created for the 2017 World Aquatics Championships held in Budapest.
-
D.
Nana
"Nana" is a popular hit single by Tanzanian Bongo Flava artist Diamond Platnumz, known for its romantic theme and widespread success across East Africa.
-
E.
Nana
Nana is an 1880 naturalist novel by Émile Zola that follows the rise and fall of a Parisian courtesan as a critique of Second Empire society.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5092ef810819093a4d1df83aeac09 |
completed | April 7, 2026, 1:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d89ff1cd948190a1ef331fb810bf26 |
completed | April 10, 2026, 7 a.m. |
Created at: April 6, 2026, 12:20 p.m.