Triple
T15749047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NCTD |
E381798
|
entity |
| Predicate | SPRINTERIs |
P57939
|
FINISHED |
| Object | diesel multiple unit light rail line |
—
|
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: diesel multiple unit light rail line | Statement: [NCTD, SPRINTERIs, diesel multiple unit light rail line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: SPRINTERIs Context triple: [NCTD, SPRINTERIs, diesel multiple unit light rail line]
-
A.
spurType
Indicates the specific kind or category of spur associated with or used by an entity.
-
B.
Typer
chosen
Indicates that one entity serves as the type or classification for another entity.
-
C.
springType
Indicates the specific kind or category of spring associated with an entity (e.g., coil, leaf, torsion).
-
D.
runnerType
Indicates the specific category or style of running associated with an entity (e.g., sprinter, marathoner, trail runner).
-
E.
commuterBrand
Indicates a relationship where a brand is specifically associated with or targeted toward commuter use or commuting contexts.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0052c6208819098165d61d378d13b |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:46 a.m.