Triple
T5717919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Auteuil |
E126066
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Caché |
E265950
|
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: Caché | Statement: [Daniel Auteuil, notableWork, Caché]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caché Context triple: [Daniel Auteuil, notableWork, Caché]
-
A.
Hidden (Caché)
chosen
Hidden (Caché) is a 2005 psychological thriller film directed by Michael Haneke, renowned for its unsettling exploration of surveillance, guilt, and bourgeois anxiety.
-
B.
Lotus Domino
Lotus Domino is IBM's enterprise-grade server platform that provides email, collaboration, and application hosting services for Lotus Notes and web clients.
-
C.
Actian
Actian is a data management and analytics company known for its hybrid data platforms and database technologies used in enterprise applications.
-
D.
VisualWorks
VisualWorks is a prominent commercial implementation of the Smalltalk programming language, known for its powerful development environment and cross-platform capabilities.
-
E.
TimesTen
TimesTen is an in-memory relational database from Oracle designed for extremely low-latency, high-throughput data management and real-time analytics.
- 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_69c0082e3d548190950169847b43043b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c024e084cc81909a652f7c10d32c32 |
completed | March 22, 2026, 5:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a7af5788190827ff8050eb6416d |
completed | March 22, 2026, 9:09 p.m. |
Created at: March 22, 2026, 3:46 p.m.