Triple
T38132412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Galactica |
E952258
|
entity |
| Predicate | hasTrains |
P202205
|
FINISHED |
| Object | 3 |
—
|
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 | Statement: [Galactica, hasTrains, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrains Context triple: [Galactica, hasTrains, 3]
-
A.
hasPassengerTrains
Indicates that a location, route, or rail line is served by trains that carry passengers.
-
B.
trainsOn
Indicates that one entity receives training, instruction, or practice using or based on another entity (such as a resource, dataset, tool, or subject).
-
C.
hasLNGTrain
Indicates that something possesses or is equipped with an LNG (liquefied natural gas) processing or transport train as part of its facilities or infrastructure.
-
D.
maintainsTrainsFor
Indicates that one entity is responsible for servicing, repairing, or otherwise keeping trains operational for another entity.
-
E.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
- 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_69f76f083548819082bd2bbf53c79e8e |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a0061454944819088a0babfe60f69fc |
completed | May 10, 2026, 10:43 a.m. |
| PD | Predicate disambiguation | batch_6a0060b9ee108190b91e8d99a16f2b30 |
completed | May 10, 2026, 10:40 a.m. |
| PDg | Predicate description generation | batch_6a0061448f6881908daa9fb0da9abefe |
completed | May 10, 2026, 10:43 a.m. |
Created at: May 3, 2026, 4:21 p.m.