Triple
T6900975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | René Goscinny |
E159491
|
entity |
| Predicate | workedWith |
P398
|
FINISHED |
| Object |
Gotlib
Gotlib was a French cartoonist and comics author renowned for his influential, often absurdist humor and for co-founding the magazine Fluide Glacial.
|
E627170
|
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: Gotlib | Statement: [René Goscinny, workedWith, Gotlib]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gotlib Context triple: [René Goscinny, workedWith, Gotlib]
-
A.
Repossi
Repossi is a high-end Italian jewelry house renowned for its avant-garde, architectural designs and strong heritage in fine jewelry craftsmanship.
-
B.
Blocket
Blocket is a major Swedish online classifieds marketplace for buying and selling goods and services, owned by the media group Schibsted.
-
C.
Librarian’s Vault
Librarian’s Vault is a secure, restricted-access chamber within the Library of Congress that houses some of the institution’s most rare, valuable, and historically significant materials.
-
D.
Ledger
Ledger is a surname most famously associated with Australian actor Heath Ledger, known for his acclaimed and influential film performances.
-
E.
Calibre
Calibre is a 2018 British thriller film about a hunting trip in the Scottish Highlands that goes disastrously wrong, starring Jack Lowden.
- 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: Gotlib Triple: [René Goscinny, workedWith, Gotlib]
Generated description
Gotlib was a French cartoonist and comics author renowned for his influential, often absurdist humor and for co-founding the magazine Fluide Glacial.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gotlib Target entity description: Gotlib was a French cartoonist and comics author renowned for his influential, often absurdist humor and for co-founding the magazine Fluide Glacial.
-
A.
Repossi
Repossi is a high-end Italian jewelry house renowned for its avant-garde, architectural designs and strong heritage in fine jewelry craftsmanship.
-
B.
Blocket
Blocket is a major Swedish online classifieds marketplace for buying and selling goods and services, owned by the media group Schibsted.
-
C.
Librarian’s Vault
Librarian’s Vault is a secure, restricted-access chamber within the Library of Congress that houses some of the institution’s most rare, valuable, and historically significant materials.
-
D.
Ledger
Ledger is a surname most famously associated with Australian actor Heath Ledger, known for his acclaimed and influential film performances.
-
E.
Calibre
Calibre is a 2018 British thriller film about a hunting trip in the Scottish Highlands that goes disastrously wrong, starring Jack Lowden.
- 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_69c6883822e0819091e321526f20ae0a |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9603f448190bb9f963c17ca206d |
completed | March 27, 2026, 7:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c748f0dc448190914e38d780644698 |
completed | March 28, 2026, 3:20 a.m. |
| NEDg | Description generation | batch_69c749f7ab5c8190ab823fac27f7484d |
completed | March 28, 2026, 3:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c74a6f828c8190bf0cc56227b1a5b2 |
completed | March 28, 2026, 3:26 a.m. |
Created at: March 27, 2026, 2:24 p.m.