Triple
T29179807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Woman’s Love and Life |
E739714
|
entity |
| Predicate | standardEnglishTitleOf |
P6688
|
FINISHED |
| Object | Frauenliebe und -leben |
—
|
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: Frauenliebe und -leben | Statement: [A Woman’s Love and Life, standardEnglishTitleOf, Frauenliebe und -leben]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardEnglishTitleOf Context triple: [A Woman’s Love and Life, standardEnglishTitleOf, Frauenliebe und -leben]
-
A.
standardTitle
Indicates that an entity has a primary or official title or name by which it is commonly recognized.
-
B.
titleInEnglish
chosen
Indicates that an entity’s title or name is given in the English language.
-
C.
hasTitleInEnglishOrthography
Indicates that an entity has a specific title expressed using English spelling and writing conventions.
-
D.
titleInLanguage
Indicates that a specific title or name is expressed in a particular language.
-
E.
hasApproximateEnglishTitle
Indicates that an entity is associated with an English title that is an approximate or non-exact rendering of its original 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_69f07cb74c2c8190ad396487fcb4fde6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc53f4f881908dcc698687bbb64d |
completed | May 3, 2026, 7:42 a.m. |
Created at: April 28, 2026, 11:56 a.m.