Triple
T8457471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MP 89 |
E199955
|
entity |
| Predicate | doorArrangement |
P4168
|
FINISHED |
| Object | 3 pairs of doors per side per car on most cars |
—
|
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: 3 pairs of doors per side per car on most cars | Statement: [MP 89, doorArrangement, 3 pairs of doors per side per car on most cars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: doorArrangement Context triple: [MP 89, doorArrangement, 3 pairs of doors per side per car on most cars]
-
A.
doorConfiguration
chosen
Indicates how a door is arranged or set up in relation to its frame, opening direction, and operational characteristics.
-
B.
doorLocation
Indicates the spatial position or placement of a door relative to a reference structure or area.
-
C.
doorType
Indicates the specific kind or category of door associated with an entity.
-
D.
doorLevel
Indicates the security or access level required to open or pass through a particular door.
-
E.
doorwayFeature
Indicates that one entity is a feature, characteristic, or structural element specifically associated with a doorway 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_69ca8318231881908fd1bc1c4d45d286 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe49064f881909391d565b97e9886 |
completed | March 31, 2026, 3:13 p.m. |
| PD | Predicate disambiguation | batch_69cbd0fc634481909842c0a30077bfde |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:10 p.m.