Triple
T35550103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lambada |
E1027330
|
entity |
| Predicate | teacherCharacterDoubleLife |
P183401
|
FINISHED |
| Object | secret Lambada dancer |
—
|
LITERAL 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: secret Lambada dancer | Statement: [Lambada, teacherCharacterDoubleLife, secret Lambada dancer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teacherCharacterDoubleLife Context triple: [Lambada, teacherCharacterDoubleLife, secret Lambada dancer]
-
A.
characterDuet
Indicates a relationship where two characters perform together as a duet in a shared scene, song, or action.
-
B.
mentorCharacter
Indicates that one character serves as a mentor, providing guidance, teaching, or support to another character.
-
C.
studentCharacter
Indicates that one entity has the role or qualities of a student in relation to another entity, typically within an educational or learning context.
-
D.
metCharacter
Indicates that one entity has encountered or been introduced to another entity at least once.
-
E.
directorCharacterOf
Indicates that a director is responsible for directing a particular character in a work (e.g., film, TV show, or play).
- F. None of above. chosen
Provenance (4 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_69f76e014fd481909e9f04ac603a2aa9 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79f7340e4819092a1a47f7028e63f |
completed | May 3, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69f79e4bdbcc8190be7a0d2cf8a77b64 |
completed | May 3, 2026, 7:13 p.m. |
| PDg | Predicate description generation | batch_69f79ec14ce08190b22cee0b40d33743 |
completed | May 3, 2026, 7:15 p.m. |
Created at: May 3, 2026, 4:04 p.m.