Triple
T376273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crown of Castile |
E8378
|
entity |
| Predicate | nobleEstate |
P11791
|
FINISHED |
| Object | Castilian nobility |
—
|
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: Castilian nobility | Statement: [Crown of Castile, nobleEstate, Castilian nobility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nobleEstate Context triple: [Crown of Castile, nobleEstate, Castilian nobility]
-
A.
hadEstate
Indicates that an entity possessed or owned a particular estate or landed property.
-
B.
landholdings
Indicates the extent or collection of land owned, controlled, or held by an entity.
-
C.
realEstateCategory
Indicates the classification of a property into a specific type or category within real estate (e.g., residential, commercial, industrial).
-
D.
occupiesFormerEstateOf
Indicates that one entity currently resides in, uses, or controls a property that was previously the estate of another entity.
-
E.
majorLandowner
Indicates that one entity owns a large or dominant portion of land in relation to another entity or area.
- 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec169a848190a577aa093c878839 |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e96351cc8190a55adf95f8c27e9e |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea0b23ec8190bef9d593162388a4 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.