Triple
T30823526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Lieutenant |
E784992
|
entity |
| Predicate | officeEquivalentTo |
P15578
|
FINISHED |
| Object | Lord Lieutenant |
—
|
NE NERFINISHED |
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: Lord Lieutenant | Statement: [Lady Lieutenant, officeEquivalentTo, Lord Lieutenant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeEquivalentTo Context triple: [Lady Lieutenant, officeEquivalentTo, Lord Lieutenant]
-
A.
equivalentOffice
chosen
Indicates that two offices are considered functionally or formally the same position, role, or authority, even if they differ in name or jurisdiction.
-
B.
officeSymbolizes
Indicates that an office represents, embodies, or stands as a symbol for a particular concept, status, authority, or organizational role.
-
C.
officeIs
Indicates that one entity serves as the office or official workplace location of another entity.
-
D.
officeSymbol
Indicates a formal code or abbreviation that identifies a specific office or organizational unit within a larger structure.
-
E.
officeUnder
Indicates that one office is subordinate to, managed by, or organizationally within the authority of another office.
- 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_69f224b6642481909e8d701de2cd1a53 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe96c2647c819082989f11e1ae3d35 |
completed | May 9, 2026, 2:06 a.m. |
| PD | Predicate disambiguation | batch_69fe928615448190af939e5a94be55bb |
completed | May 9, 2026, 1:48 a.m. |
Created at: April 29, 2026, 8:44 p.m.