Triple
T35932219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Levens Hall |
E1039195
|
entity |
| Predicate | hasSignificantRebuilding |
P145013
|
FINISHED |
| Object | late 17th century |
—
|
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: late 17th century | Statement: [Levens Hall, hasSignificantRebuilding, late 17th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSignificantRebuilding Context triple: [Levens Hall, hasSignificantRebuilding, late 17th century]
-
A.
hasMajorReconstruction
Indicates that an entity has undergone a significant or extensive reconstruction or renovation.
-
B.
largelyRebuilt
Indicates that an entity has been substantially reconstructed or renovated, with most of its original structure replaced or significantly altered.
-
C.
hasReconstructionWork
Indicates that an entity is undergoing, has undergone, or is associated with reconstruction or restoration work.
-
D.
rebuiltOrExpanded
Indicates that one entity has been reconstructed, enlarged, or otherwise significantly developed from its previous form or state.
-
E.
rebuiltOrModifiedDuring
chosen
Indicates that an existing entity was reconstructed, renovated, or otherwise significantly altered during a specified time period or event.
- 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_69f76e23e4688190a5369138755138bf |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fe00dad1708190b6522476bebb43af |
completed | May 8, 2026, 3:27 p.m. |
| PD | Predicate disambiguation | batch_69fdfc3717f48190bb50ac2919c8ef95 |
completed | May 8, 2026, 3:07 p.m. |
Created at: May 3, 2026, 4:07 p.m.