Triple
T5564267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | J’en ai marre! |
E145841
|
entity |
| Predicate | translatedTitleEnglish |
P6688
|
FINISHED |
| Object | I’m fed up! |
—
|
LITERAL 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: I’m fed up! | Statement: [J’en ai marre!, translatedTitleEnglish, I’m fed up!]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: translatedTitleEnglish Context triple: [J’en ai marre!, translatedTitleEnglish, I’m fed up!]
-
A.
titleInEnglish
chosen
Indicates that an entity’s title or name is given in the English language.
-
B.
translationTitle
Indicates that one entity is the title assigned to a translated version of another entity (such as a work, document, or text).
-
C.
officialTitleInLanguage
Indicates that an entity’s official title or designation is expressed in a specified language.
-
D.
internationalTitle
Indicates that an entity has a title or name used in international or cross-border contexts, distinct from its local or original title.
-
E.
equivalentTitleInJapanese
Indicates that one entity has a corresponding or matching title in Japanese that is equivalent in meaning or usage to the other entity’s title.
- F. None of above.
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_69c008fdae24819081aa002ad99cd966 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c02032330c819094f2bc1e8c93a5b6 |
completed | March 22, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69c01b12826c8190969a584d0f53aa44 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:36 p.m.