Triple
T12919374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Father of the Bride Part II |
E309072
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Franck Eggelhoffer |
E313592
|
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: Franck Eggelhoffer | Statement: [Father of the Bride Part II, featuresCharacter, Franck Eggelhoffer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Franck Eggelhoffer Context triple: [Father of the Bride Part II, featuresCharacter, Franck Eggelhoffer]
-
A.
Franck Eggelhoffer
chosen
Franck Eggelhoffer is the flamboyant, eccentric wedding planner portrayed by Martin Short in the comedy film "Father of the Bride."
-
B.
Rudy Bourgarel
Rudy Bourgarel is a former French basketball player best known as the father of NBA star Rudy Gobert.
-
C.
Benoit Dageville
Benoit Dageville is a French computer scientist and entrepreneur best known as a co-founder of the cloud data platform company Snowflake.
-
D.
Philippe Knoche
Philippe Knoche is a French business executive best known for leading the nuclear energy group Areva through a major restructuring of France’s atomic industry.
-
E.
Thierry Burkhard
Thierry Burkhard is a French Army general who has served as France’s top military officer and a key figure in shaping the country’s contemporary defense policy and armed forces.
- 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_69d7bdf92b588190acdf2a2291ac4590 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971e6d9fc8190b8a5244b26b5f78a |
completed | April 10, 2026, 9:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e262580c8190ad3f1aa77fd0674c |
completed | May 3, 2026, 5:51 a.m. |
Created at: April 9, 2026, 5:41 p.m.