Triple
T29097265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Virginian |
E735041
|
entity |
| Predicate | featureInPlot |
P80690
|
FINISHED |
| Object | birthplace of 1900 |
—
|
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: birthplace of 1900 | Statement: [SS Virginian, featureInPlot, birthplace of 1900]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featureInPlot Context triple: [SS Virginian, featureInPlot, birthplace of 1900]
-
A.
displaysFeature
Indicates that one entity presents, shows, or makes visible a particular feature or characteristic of another entity.
-
B.
featuresIn
chosen
Indicates that an entity appears or plays a role within another entity, such as a person or element being included in a work, event, or context.
-
C.
featuresMode
Indicates that one entity operates in, supports, or is characterized by a particular mode or configuration specified by another entity.
-
D.
featuresDemon
Indicates that an entity includes, depicts, or prominently involves a demon.
-
E.
featuresSample
Indicates that an entity includes or presents a particular sample as one of its components or examples.
- 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_69f05b0ed66481908f2e864fa550d2f1 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69ff17be6ad48190963206f2619b1b28 |
completed | May 9, 2026, 11:17 a.m. |
| PD | Predicate disambiguation | batch_69ff1724ba24819092c928fcbcb286ec |
completed | May 9, 2026, 11:14 a.m. |
Created at: April 28, 2026, 11:09 a.m.