Triple
T164976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GG1 electric locomotive |
E2993
|
entity |
| Predicate | currentCollectionMethod |
P5625
|
FINISHED |
| Object | 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: pantograph | Statement: [GG1 electric locomotive, currentCollectionMethod, pantograph]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: currentCollectionMethod Context triple: [GG1 electric locomotive, currentCollectionMethod, pantograph]
-
A.
hasCollection
Indicates that an entity possesses, maintains, or is associated with a set or group of related items treated as a collection.
-
B.
appointmentMethod
Indicates how an appointment is arranged, such as the channel, process, or means used to schedule it.
-
C.
collectionSize
Indicates the total number of items contained within a specified collection.
-
D.
collectsFrom
Indicates that one entity gathers, receives, or takes something (such as items, data, or payments) from another entity.
-
E.
distributionMethod
Indicates the means or channel through which something (such as a product, resource, or information) is delivered or made available to recipients.
- F. None of above. chosen
Provenance (4 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_69a2524ce1e48190ab066bf72859f474 |
completed | Feb. 28, 2026, 2:26 a.m. |
| NER | Named-entity recognition | batch_69a258827da481909b20ea5e9d21676f |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a25664ba8081908ac298511a9fc5ba |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a256eb46ec81909c730000e5041d0d |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:34 a.m.