Triple
T24856209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Earl of Uxbridge |
E622033
|
entity |
| Predicate | subsequentTitle |
P143400
|
FINISHED |
| Object | Marquess of Anglesey |
—
|
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: Marquess of Anglesey | Statement: [Earl of Uxbridge, subsequentTitle, Marquess of Anglesey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subsequentTitle Context triple: [Earl of Uxbridge, subsequentTitle, Marquess of Anglesey]
-
A.
nextTitleType
Indicates the type or category of the title that immediately follows another title in a sequence or series.
-
B.
titleContinuesAs
chosen
Indicates that one title is succeeded or carried on by another title as its continuation.
-
C.
laterTitleHolder
Indicates that one entity is a subsequent holder of a particular title or position previously held by another entity.
-
D.
successorSeriesTitle
Indicates that one series is the direct follow-up or continuation to another series in sequence.
-
E.
previousTitle
Indicates that one title held or used by an entity directly preceded another title in sequence or time.
- 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_69e2fac350d08190b3affde1b451a8c5 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f44a417a58819081777e18dda149fd |
completed | May 1, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69f442b8479c8190a7c8e416ac9e28a0 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 5:21 a.m.