Triple
T29318336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ballynegall House, County Westmeath |
E743440
|
entity |
| Predicate | hasFacadeCharacter |
P181236
|
FINISHED |
| Object | formal classical composition |
—
|
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: formal classical composition | Statement: [Ballynegall House, County Westmeath, hasFacadeCharacter, formal classical composition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFacadeCharacter Context triple: [Ballynegall House, County Westmeath, hasFacadeCharacter, formal classical composition]
-
A.
hasFacadeSystem
Indicates that one entity possesses or is equipped with a particular façade system as part of its structure or design.
-
B.
hasFacadeBy
Indicates that one entity’s façade (front-facing exterior surface) is designed, created, or provided by another entity.
-
C.
hasDemonCharacter
Indicates that an entity includes or features a character that is a demon.
-
D.
hasPrimaryCharacter
Indicates that an entity features another entity as its main or central character.
-
E.
hasPuppetCharacter
Indicates that one entity features, includes, or is associated with a particular puppet character as part of its content or composition.
- 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_69f0912502c8819087d9e8398ee991a8 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f7675b12848190a3569cfda29c5b0e |
completed | May 3, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69f762f4b59481909f70074f11825bfb |
completed | May 3, 2026, 3 p.m. |
| PDg | Predicate description generation | batch_69f76759b3c48190ad8f1b33596f98c4 |
completed | May 3, 2026, 3:18 p.m. |
Created at: April 28, 2026, 1:21 p.m.