Triple
T33979946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Odakyu 3000 series EMU |
E871248
|
entity |
| Predicate | pantographType |
P111725
|
FINISHED |
| Object | single-arm pantograph |
—
|
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: single-arm pantograph | Statement: [Odakyu 3000 series EMU, pantographType, single-arm pantograph]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pantographType Context triple: [Odakyu 3000 series EMU, pantographType, single-arm pantograph]
-
A.
hasPantograph
chosen
Indicates that one entity is equipped with or possesses a pantograph used for drawing power or making contact with an overhead system.
-
B.
pantographModification
Indicates a modification or alteration made to a pantograph mechanism in relation to another entity or system.
-
C.
bogieType
Indicates the specific configuration or classification of a vehicle’s bogie (wheel assembly) used in its design or operation.
-
D.
catapultType
Indicates the specific kind or category of catapult associated with an entity or event.
-
E.
propellerType
Indicates the specific kind or classification of propeller associated with an 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_69f3499da0188190ab1a4ff06fb06a2a |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7064e906881909c3186c646145d34 |
completed | May 3, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69f70100ec1c8190a6b97f50e88891f2 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 1:50 a.m.