Triple
T2163335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T1 subway train |
E46849
|
entity |
| Predicate | interiorLayout |
P32581
|
FINISHED |
| Object | longitudinal seating |
—
|
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: longitudinal seating | Statement: [T1 subway train, interiorLayout, longitudinal seating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interiorLayout Context triple: [T1 subway train, interiorLayout, longitudinal seating]
-
A.
interiorStyle
Indicates that one entity has a particular interior design style or aesthetic characterized by the other entity.
-
B.
interiorFloor
Indicates that one entity is the interior floor surface or flooring of another enclosing space or structure.
-
C.
interiorSize
Indicates the size or dimensions of the inside space of an object or structure.
-
D.
hasInteriorFeature
Indicates that an entity contains or includes a specific feature within its interior space.
-
E.
layoutDetail
chosen
Indicates the specific arrangement or configuration details of how elements are laid out in relation to each other.
- 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_69a88a184cbc8190877791f6552c2484 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe8d105c819098371c35c88873dc |
completed | March 7, 2026, 5:58 a.m. |
| PD | Predicate disambiguation | batch_69abbd9c90408190b6b65498ca43ce26 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:45 p.m.