Triple
T5036806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silver Lady |
E113444
|
entity |
| Predicate | hasEraAssociation |
P36399
|
FINISHED |
| Object | mid-20th-century American passenger rail |
—
|
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: mid-20th-century American passenger rail | Statement: [Silver Lady, hasEraAssociation, mid-20th-century American passenger rail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEraAssociation Context triple: [Silver Lady, hasEraAssociation, mid-20th-century American passenger rail]
-
A.
appliesToEra
Indicates that something is relevant, valid, or in effect during a particular historical or temporal era.
-
B.
representsEra
chosen
Indicates that one entity designates the historical era, period, or age to which another entity belongs or is associated.
-
C.
associatedWithArtistEra
Indicates a relationship where an artist is linked to a particular artistic era or period with which their work or influence is identified.
-
D.
partOfEra
Indicates that one entity exists as a temporal segment or component within the duration or scope of a larger historical era.
-
E.
followsEra
Indicates that one time period or era comes directly after another in chronological order.
- 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_69bd44384298819089c49e7c330ec7b8 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd73bb069c8190af86f1b2f95f3d95 |
completed | March 20, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_69bd71529d608190a53470ba6c14bb1d |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:37 p.m.