Triple
T5693596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Wedding Banquet |
E125482
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Mader |
E539308
|
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: Mader | Statement: [The Wedding Banquet, musicBy, Mader]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mader Context triple: [The Wedding Banquet, musicBy, Mader]
-
A.
Mader
chosen
Mader is a composer best known for creating the musical score for the Taiwanese film "Eat Drink Man Woman."
-
B.
Collip
Collip is a surname most notably associated with James Collip, a Canadian biochemist who was part of the team that developed insulin as a treatment for diabetes.
-
C.
Stearns
Stearns is the middle name of the influential modernist poet and critic T. S. Eliot, whose full name is Thomas Stearns Eliot.
-
D.
Stavertonia
Stavertonia is a residential annexe of University College, Oxford, providing modern accommodation and facilities for its students.
-
E.
Merian
Merian is a given name most notably borne by Merian C. Cooper, the American filmmaker and co-creator of the classic movie "King Kong."
- 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_69c0082bb19c8190823a4facd3cba79b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c023e7dbe48190850b501f223614e3 |
completed | March 22, 2026, 5:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07dd76f008190970c3b17ec8cbfd8 |
completed | March 22, 2026, 11:40 p.m. |
Created at: March 22, 2026, 3:44 p.m.