Triple
T23501936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Poor People of Paris |
E571871
|
entity |
| Predicate | hasOriginalFrenchTitle |
P13516
|
FINISHED |
| Object | La Goualante du pauvre Jean |
—
|
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: La Goualante du pauvre Jean | Statement: [The Poor People of Paris, hasOriginalFrenchTitle, La Goualante du pauvre Jean]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginalFrenchTitle Context triple: [The Poor People of Paris, hasOriginalFrenchTitle, La Goualante du pauvre Jean]
-
A.
hasOriginalCountryTitle
Indicates that an entity is associated with the title it originally had in its country of origin.
-
B.
hasOriginalTitleScript
Indicates that an entity’s original title is written or represented in a specific writing system or script.
-
C.
originalLanguageTitle
chosen
Indicates the title of a work as it appears in its original language of creation or publication.
-
D.
hasOriginalTitleMeaning
Indicates that an entity’s original title conveys or is associated with a particular meaning or interpretation.
-
E.
originalTitleLanguage
Indicates the language in which a work’s original title was written or expressed.
- 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_69e245b4829881909b77a70e942bbd54 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a8fd65e08190ae94ad4f0638cc0e |
completed | April 29, 2026, 6:45 a.m. |
| PD | Predicate disambiguation | batch_69f0621165c08190a0b27b1319733959 |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 6:06 p.m.