Triple
T5228195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trust in Me |
E118043
|
entity |
| Predicate | characterSungBy |
P14884
|
FINISHED |
| Object | Kaa |
E201573
|
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: Kaa | Statement: [Trust in Me, characterSungBy, Kaa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaa Context triple: [Trust in Me, characterSungBy, Kaa]
-
A.
Kaa
chosen
Kaa is a giant, hypnotic python who serves as a dangerous and manipulative predator in Disney’s live-action adaptation of The Jungle Book.
-
B.
Käina
Käina is a small settlement on the Estonian island of Hiiumaa, known for its coastal landscapes and traditional rural character.
-
C.
Kukawa
Kukawa is a historic town in northeastern Nigeria that once served as the political and cultural center of the Kanuri people and the Bornu Empire.
-
D.
Kile
Kile is a KDE-based integrated LaTeX editor that provides tools for writing, compiling, and previewing LaTeX documents efficiently.
-
E.
Kasoa
Kasoa is a rapidly growing urban town in southern Ghana that serves as a major residential and commercial hub on the outskirts of Accra.
- 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_69bd4466fb8c819083b806a79414d7e4 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7adee36881909b034b8735db9d67 |
completed | March 20, 2026, 4:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf06b46eac81908b985363733fcd63 |
completed | March 21, 2026, 8:59 p.m. |
Created at: March 20, 2026, 1:48 p.m.