Triple
T8092680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bléone River |
E188905
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object |
Caché
Caché is a tributary stream that feeds into the Bléone River in southeastern France.
|
E711788
|
NE FINISHED |
How this triple was built (4 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: [Bléone River, hasTributary, Caché]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caché Context triple: [Bléone River, hasTributary, Caché]
-
A.
Hidden (Caché)
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. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Caché Triple: [Bléone River, hasTributary, Caché]
Generated description
Caché is a tributary stream that feeds into the Bléone River in southeastern France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Caché Target entity description: Caché is a tributary stream that feeds into the Bléone River in southeastern France.
-
A.
Hidden (Caché)
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. chosen
Provenance (5 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_69ca82b7b3e88190b9041ab0ef28b3cb |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb42217a1881909792b08a2f06fb75 |
completed | March 31, 2026, 3:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc64112138819096050975d707d8ee |
completed | April 1, 2026, 12:17 a.m. |
| NEDg | Description generation | batch_69cc68647cec81909736383fbe73d2e8 |
completed | April 1, 2026, 12:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc69b93bbc8190be2338182dd57b17 |
completed | April 1, 2026, 12:41 a.m. |
Created at: March 30, 2026, 5:30 p.m.