Triple
T26829792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Encaenia ceremony |
E675466
|
entity |
| Predicate | usesVenueDesignedBy |
P162360
|
FINISHED |
| Object | Christopher Wren |
—
|
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: Christopher Wren | Statement: [Encaenia ceremony, usesVenueDesignedBy, Christopher Wren]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesVenueDesignedBy Context triple: [Encaenia ceremony, usesVenueDesignedBy, Christopher Wren]
-
A.
homeVenueAlsoUsedBy
Indicates that the venue serving as a home location for one entity is also used as a venue by another entity.
-
B.
usesVenues
Indicates that one entity makes use of or operates within specific venues or locations to carry out its activities or services.
-
C.
restaurantDesignedBy
Indicates that a restaurant was created or planned by a particular designer or architect.
-
D.
developedVenue
Indicates that an entity was responsible for creating, constructing, or significantly establishing a particular venue.
-
E.
hostVenueInstanceOf
Indicates that a specific host venue is an instance or concrete realization of a more general venue type or category.
- 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_69eee9b776448190993a60b67fcc9545 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f6250321088190ae3ed1dc9f2fcd03 |
completed | May 2, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69f623a7539c8190b71797f583da9f63 |
completed | May 2, 2026, 4:17 p.m. |
| PDg | Predicate description generation | batch_69f62473a38481909b919f88ffb5b492 |
completed | May 2, 2026, 4:21 p.m. |
Created at: April 27, 2026, 5 a.m.