Triple
T24014842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Prophète |
E594643
|
entity |
| Predicate | operaHouseType |
P154872
|
FINISHED |
| Object | Paris Grand Opera |
—
|
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: Paris Grand Opera | Statement: [Le Prophète, operaHouseType, Paris Grand Opera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operaHouseType Context triple: [Le Prophète, operaHouseType, Paris Grand Opera]
-
A.
operaHouseCapacity
Indicates the maximum number of people that an opera house is designed or allowed to accommodate.
-
B.
hasOperaHouseAssociation
Indicates a relationship where an entity is connected or related to an opera house, such as through location, ownership, operation, affiliation, or significant involvement.
-
C.
hasOperaHouse
Indicates that one entity possesses, contains, or is the location of an opera house.
-
D.
operaFestivalVenue
Indicates that a venue is the location where an opera festival is held.
-
E.
operaHouseOfPremiere
Indicates the opera house where a particular work was first premiered or originally performed.
- F. None of above. chosen
Provenance (4 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_69e288bc8f608190ac4af29f0bd1c744 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d5a32374819094dcb42abf18c033 |
completed | April 29, 2026, 9:55 a.m. |
| PD | Predicate disambiguation | batch_69f17639d23c8190bed93434e2f9230a |
completed | April 29, 2026, 3:08 a.m. |
| PDg | Predicate description generation | batch_69f17c28b684819084eea522126463f8 |
completed | April 29, 2026, 3:34 a.m. |
Created at: April 17, 2026, 9:42 p.m.