Triple
T37217264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baron Maude of Horsham |
E922773
|
entity |
| Predicate | granteeReformArea |
P148277
|
FINISHED |
| Object | civil service reform |
—
|
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: civil service reform | Statement: [Baron Maude of Horsham, granteeReformArea, civil service reform]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: granteeReformArea Context triple: [Baron Maude of Horsham, granteeReformArea, civil service reform]
-
A.
reformsArea
Indicates that an entity is responsible for changing, improving, or restructuring a particular area or domain.
-
B.
notableGrantArea
Indicates that an entity is recognized for providing significant grants or funding within a particular area or field.
-
C.
governanceArea
Indicates the geographic or jurisdictional area over which an entity has governing authority or responsibility.
-
D.
landGrantedBy
Indicates that one party has given or transferred legal rights to a piece of land to another party.
-
E.
hasKeyReformArea
chosen
Indicates that an entity is associated with or involves a primary or central area of reform.
- 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_69f76ea6f5288190b8d9988f613811c0 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
Created at: May 3, 2026, 4:15 p.m.