Triple
T18759477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holocaust Memorial (Nameless Library, Vienna) |
E458731
|
entity |
| Predicate | unveiledByPosition |
P133433
|
FINISHED |
| Object | President of Austria |
—
|
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: President of Austria | Statement: [Holocaust Memorial (Nameless Library, Vienna), unveiledByPosition, President of Austria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: unveiledByPosition Context triple: [Holocaust Memorial (Nameless Library, Vienna), unveiledByPosition, President of Austria]
-
A.
knownForPosition
Indicates that an entity is notably recognized or distinguished for holding a particular position, role, or office.
-
B.
positionInShow
Indicates the specific order or placement an entity occupies within a show, series, or sequence of performances or episodes.
-
C.
initiallyPositionedAs
Indicates that one entity’s starting or original position is specified relative to another entity or reference frame.
-
D.
positionInLent
Indicates the specific point or stage an event, day, or period occupies within the overall timeline of Lent.
-
E.
positionInCase
Indicates the specific role, status, or placement that an entity holds within a particular case or legal proceeding.
- 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_69d8d395dba0819087568404508590cb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e58d7db2f48190a4f1c5c9801fe180 |
completed | April 20, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69e48d0b7b708190877951b6e6cdcbc4 |
completed | April 19, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e49a9bcc0c81908df3e513fd6762ff |
completed | April 19, 2026, 9:04 a.m. |
Created at: April 10, 2026, 11:52 a.m.