Triple
T1038772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort Henry |
E22422
|
entity |
| Predicate | restoredAs |
P4143
|
FINISHED |
| Object | living history museum |
—
|
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: living history museum | Statement: [Fort Henry, restoredAs, living history museum]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: restoredAs Context triple: [Fort Henry, restoredAs, living history museum]
-
A.
restored
Indicates that an entity has returned another entity to a previous or improved state, condition, or position after damage, loss, or alteration.
-
B.
restoredBy
Indicates that an entity has been returned to a previous or improved state through the actions or intervention of another entity.
-
C.
hasRestoration
Indicates that an entity has undergone, is undergoing, or is associated with a process of repair, renewal, or restoration.
-
D.
reconstructedAs
chosen
Indicates that one entity has been rebuilt, recreated, or inferred based on evidence, models, or partial information from another entity.
-
E.
officeRestoredIn
Indicates that an office or official position was reinstated or brought back into effect at a particular time or in a specific context.
- 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_69a493d91478819094cc01fb65564bc1 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b97c64a88190bf1119fdd4940bf3 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b729f8488190b2042bd9c625a833 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:41 p.m.