Triple
T29800090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucia di Lammermoor |
E756666
|
entity |
| Predicate | FrenchVersionPremierePlace |
P32700
|
FINISHED |
| Object | Théâtre de la Renaissance, Paris |
—
|
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: Théâtre de la Renaissance, Paris | Statement: [Lucia di Lammermoor, FrenchVersionPremierePlace, Théâtre de la Renaissance, Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: FrenchVersionPremierePlace Context triple: [Lucia di Lammermoor, FrenchVersionPremierePlace, Théâtre de la Renaissance, Paris]
-
A.
firstFrenchPremiereLocation
chosen
Indicates the location where an entity had its first premiere or initial public showing in France.
-
B.
primaryFrenchDestination
Indicates that one entity is the main or most significant travel destination in France for another entity.
-
C.
FrenchEditionURL
Indicates the URL where the French-language edition or version of an entity can be accessed.
-
D.
firstFrenchPremiereDate
Indicates the date on which something (such as a work or event) was first premiered or publicly presented in France.
-
E.
isFrancophoneCounterpartOf
Indicates that one entity serves as the French-speaking or French-language equivalent or counterpart of another entity.
- 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_69f22454583081908927516cb9938d1d |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f67525c9a0819084e47299fa5dabfe |
completed | May 2, 2026, 10:05 p.m. |
| PD | Predicate disambiguation | batch_69f66ec5bf508190ad088b89455252bd |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 5:17 p.m.