Triple
T936291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M7 electric multiple unit |
E20201
|
entity |
| Predicate | hasDoorConfiguration |
P4168
|
FINISHED |
| Object | multiple side doors per car |
—
|
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: multiple side doors per car | Statement: [M7 electric multiple unit, hasDoorConfiguration, multiple side doors per car]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDoorConfiguration Context triple: [M7 electric multiple unit, hasDoorConfiguration, multiple side doors per car]
-
A.
doorConfiguration
chosen
Indicates how a door is arranged or set up in relation to its frame, opening direction, and operational characteristics.
-
B.
doorType
Indicates the specific kind or category of door associated with an entity.
-
C.
numberOfDoors
Indicates the quantity of doors associated with an entity.
-
D.
hasInteriorFeature
Indicates that an entity contains or includes a specific feature within its interior space.
-
E.
hasCabinet
Indicates that one entity possesses, includes, or is equipped with a cabinet associated with it.
- 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_69a493b0270c81909e6c9ce310f6aa55 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b36558588190a2a9c710073624d1 |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b29b245c8190b143f28b77fede3c |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.