Triple
T37836987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château des Milandes |
E943364
|
entity |
| Predicate | builtForFamily |
P189261
|
FINISHED |
| Object | Lords of Caumont |
—
|
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: Lords of Caumont | Statement: [Château des Milandes, builtForFamily, Lords of Caumont]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: builtForFamily Context triple: [Château des Milandes, builtForFamily, Lords of Caumont]
-
A.
isFamilyFriendly
Indicates that something is suitable for all ages and does not contain content inappropriate for children or sensitive audiences.
-
B.
worksForFamily
Indicates that one entity is employed by or performs work on behalf of another entity that is a family member or family unit.
-
C.
goodWithChildren
Indicates that an entity interacts with, behaves around, or cares for children in a positive, safe, and appropriate manner.
-
D.
familyIncluded
Indicates that one entity’s family members are included within the scope, coverage, or membership defined by the other entity.
-
E.
hasKidFriendlyFeatures
Indicates that something possesses characteristics, amenities, or design elements that are suitable and appealing for children.
- 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_69f76eeb0f7081908d6d3adbc469889c |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbbae559a8819086ef839973f8d9b2 |
completed | May 6, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69fbb1440fa08190abf25ba684f75b6e |
completed | May 6, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69fbbae3fc508190adff3d7abbf107a4 |
completed | May 6, 2026, 10:04 p.m. |
Created at: May 3, 2026, 4:19 p.m.