Triple
T37226497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Cat and Jerry Mouse |
E923016
|
entity |
| Predicate | knownInFrenchAs |
P6538
|
FINISHED |
| Object | Tom et Jerry |
—
|
NE NERFINISHED |
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: Tom et Jerry | Statement: [Tom Cat and Jerry Mouse, knownInFrenchAs, Tom et Jerry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knownInFrenchAs Context triple: [Tom Cat and Jerry Mouse, knownInFrenchAs, Tom et Jerry]
-
A.
nameInFrench
chosen
Indicates that an entity is known or referred to by a specific name expressed in the French language.
-
B.
isFrancophoneCounterpartOf
Indicates that one entity serves as the French-speaking or French-language equivalent or counterpart of another entity.
-
C.
hasOfficialFrenchName
Indicates that an entity possesses an officially recognized name in the French language.
-
D.
hasFrenchWikipediaPage
Indicates that the subject entity has a dedicated article on the French-language version of Wikipedia.
-
E.
knownInLanguage
Indicates that an entity is recognized, named, or expressed in a particular language.
- 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_69f76ea7f0008190b31b8e30f3d05a71 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb78cbef988190b8f79d946b46e6b2 |
completed | May 6, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69fb5a9ac5a08190b24ef308963fc52b |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 3, 2026, 4:15 p.m.