Triple
T31294869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Beef Carcass |
E798042
|
entity |
| Predicate | hasTitleInOtherLanguage |
P89513
|
FINISHED |
| Object | Carcass of Beef |
—
|
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: Carcass of Beef | Statement: [The Beef Carcass, hasTitleInOtherLanguage, Carcass of Beef]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleInOtherLanguage Context triple: [The Beef Carcass, hasTitleInOtherLanguage, Carcass of Beef]
-
A.
hasTitleInLanguage
Indicates that an entity has a specific title expressed in a particular language.
-
B.
equivalentTitleInLanguage
Indicates that two titles are equivalent in meaning or reference, but expressed in a specified language.
-
C.
hasTitleInEnglishOrthography
Indicates that an entity has a specific title expressed using English spelling and writing conventions.
-
D.
titleInLanguage
chosen
Indicates that a specific title or name is expressed in a particular language.
-
E.
hasTitleInTransliteration
Indicates that an entity has a specific title represented in a transliterated form from another writing system.
- 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_69f224dfde288190af313f3c221c857e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fcc4b700748190ae00b21d09c96695 |
completed | May 7, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fcb0f9d3d881908a049475182fb039 |
completed | May 7, 2026, 3:34 p.m. |
Created at: April 29, 2026, 9:14 p.m.