Triple
T1074422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chair Ñ |
E23802
|
entity |
| Predicate | seatDesignationSystem |
P21980
|
FINISHED |
| Object | letters of the Spanish alphabet |
—
|
LITERAL FINISHED |
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: letters of the Spanish alphabet | Statement: [Chair Ñ, seatDesignationSystem, letters of the Spanish alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatDesignationSystem Context triple: [Chair Ñ, seatDesignationSystem, letters of the Spanish alphabet]
-
A.
seatNotationSystem
chosen
Indicates the system or convention used to label, number, or otherwise denote seats within a venue or vehicle.
-
B.
seatLocation
Indicates the spatial position or placement of a seat relative to a reference point or environment.
-
C.
seatCategory
Indicates the classification or type of a seat (e.g., by comfort level, price tier, or section) assigned to an entity.
-
D.
seatTraditionallyAssociated
Indicates that one entity is a seat or position that is customarily or historically linked with another entity, such as a role, office, or title.
-
E.
seatingConfiguration
Indicates how seats are arranged or organized relative to each other in a given context.
- 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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b92cbfd481909e2f928c1d06ebaa |
completed | March 1, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69a4b73ba8208190be7f3cef8c18689b |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.