Triple
T13987192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Disney's Wedding Pavilion |
E336469
|
entity |
| Predicate | hasAltarArea |
P67014
|
FINISHED |
| Object | front altar with castle view |
—
|
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: front altar with castle view | Statement: [Disney's Wedding Pavilion, hasAltarArea, front altar with castle view]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAltarArea Context triple: [Disney's Wedding Pavilion, hasAltarArea, front altar with castle view]
-
A.
hasAltar
Indicates that one entity possesses, contains, or includes an altar as part of its features or components.
-
B.
hasAltarLocation
chosen
Indicates that an altar is situated at or associated with a specific location.
-
C.
hasAltarType
Indicates that an entity is associated with or characterized by a specific type or category of altar.
-
D.
hasAltarDedication
Indicates that an altar is dedicated to, in honor of, or in association with a particular entity or purpose.
-
E.
hasRitualSpace
Indicates that an entity possesses or is associated with a designated space used for ritual or ceremonial activities.
- 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ea537408190bb9d35963886803f |
completed | April 14, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69dd465dfbc4819090d8c61fd572d35f |
completed | April 13, 2026, 7:39 p.m. |
Created at: April 9, 2026, 10:18 p.m.