Triple
T26760000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lowood School |
E674773
|
entity |
| Predicate | afterReformStatus |
P163891
|
FINISHED |
| Object | healthier institution |
—
|
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: healthier institution | Statement: [Lowood School, afterReformStatus, healthier institution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: afterReformStatus Context triple: [Lowood School, afterReformStatus, healthier institution]
-
A.
legalStatusAfterReform
Indicates the legal status or condition an entity holds following the implementation of a specific reform or legal change.
-
B.
replacedInReform
Indicates that one entity was substituted or superseded by another as part of a formal reform or restructuring process.
-
C.
lastReform
Indicates the most recent reform or change that was applied to an entity, typically linking the entity to its latest reform event or version.
-
D.
countryAfterReform
Indicates that one country entity represents the state of that country after a specified reform or transformation has taken place.
-
E.
scriptAfterReform
Indicates that one script or writing system is used after a reform or modification has been applied to another script.
- 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_69eecda6e9dc81908452fab3ba17ed9b |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f6416fbf4081909b0913c337927fc4 |
completed | May 2, 2026, 6:24 p.m. |
| PD | Predicate disambiguation | batch_69f63c663be481908f233d25d28713a4 |
completed | May 2, 2026, 6:03 p.m. |
| PDg | Predicate description generation | batch_69f63fd4f7448190930c723ba7cfce62 |
completed | May 2, 2026, 6:17 p.m. |
Created at: April 27, 2026, 3:57 a.m.