Triple
T20269628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shadowland |
E499059
|
entity |
| Predicate | performerInStory |
P42552
|
FINISHED |
| Object | Nala |
—
|
NE NERFINISHED |
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: Nala | Statement: [Shadowland, performerInStory, Nala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nala Context triple: [Shadowland, performerInStory, Nala]
-
A.
Nala
chosen
Nala is a courageous lioness from Disney's "The Lion King," known as Simba's childhood friend and later queen of the Pride Lands.
-
B.
Nala
Nala is a legendary king in Hindu mythology, renowned for his righteousness, skill with horses, and central role in the love story of Nala and Damayanti in the Mahabharata.
-
C.
Sheba
Sheba is a biblical figure traditionally associated with a people or kingdom in the ancient Near East, often linked to the famed Queen of Sheba.
-
D.
Faline
Faline is a young doe in Disney's animated film "Bambi," known as Bambi's childhood friend and later his mate.
-
E.
Beti-Fang
Beti-Fang is a cluster of closely related Bantu languages spoken primarily in Cameroon, Equatorial Guinea, and Gabon by the Beti and Fang peoples.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e675dc8e708190b840d687f134c9e8 |
completed | April 20, 2026, 6:52 p.m. |
Created at: April 11, 2026, 11:42 p.m.