Triple
T12948634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House of Spee |
E309831
|
entity |
| Predicate | hasTraditionalResidence |
P79353
|
FINISHED |
| Object | Rhineland estates |
—
|
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: Rhineland estates | Statement: [House of Spee, hasTraditionalResidence, Rhineland estates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalResidence Context triple: [House of Spee, hasTraditionalResidence, Rhineland estates]
-
A.
hasTraditionalResidenceCountry
chosen
Indicates that an entity’s customary or long-term country of residence is the specified country.
-
B.
hasResidenceIn
Indicates that an entity lives or maintains a primary dwelling in a specified location.
-
C.
hasCanonicalResidence
Indicates that an entity has an officially recognized primary place of residence or domicile.
-
D.
hasExclusiveResidence
Indicates that an entity resides in exactly one specific place and has no other concurrent residences.
-
E.
hasNearbyFormerResidenceOf
Indicates that one entity is located near a place that used to be the residence of 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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97db69f548190a1a693bc0d6c191a |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:43 p.m.