Triple
T30823698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Head of the House of Habsburg-Lorraine |
E784996
|
entity |
| Predicate | seatTraditionallyIn |
P16984
|
FINISHED |
| Object | Vienna |
—
|
NE NERFINISHED |
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: Vienna | Statement: [Head of the House of Habsburg-Lorraine, seatTraditionallyIn, Vienna]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatTraditionallyIn Context triple: [Head of the House of Habsburg-Lorraine, seatTraditionallyIn, Vienna]
-
A.
seatTraditionallyAssociated
chosen
Indicates that one entity is a seat or position that is customarily or historically linked with another entity, such as a role, office, or title.
-
B.
seatOn
Indicates that one entity is positioned or placed on a seat or seating surface associated with another entity.
-
C.
seatSometimesLocatedIn
Indicates that the usual or primary seat of something is only occasionally or intermittently located within a given place or container.
-
D.
seatIs
Indicates that one entity functions as the seat or seating position of another entity.
-
E.
seatForm
Indicates that one entity serves as the physical seating structure or configuration associated with another entity.
- 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_69f224b6642481909e8d701de2cd1a53 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f690f3d1dc8190bba161d92fd2065d |
completed | May 3, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69f68b7d2794819092fef8a63f4f3de8 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 8:44 p.m.