Triple
T30199383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baron Jeffreys of Wem |
E767729
|
entity |
| Predicate | titleNumberOfFirstHolder |
P195233
|
FINISHED |
| Object | 1st Baron Jeffreys |
—
|
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: 1st Baron Jeffreys | Statement: [Baron Jeffreys of Wem, titleNumberOfFirstHolder, 1st Baron Jeffreys]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleNumberOfFirstHolder Context triple: [Baron Jeffreys of Wem, titleNumberOfFirstHolder, 1st Baron Jeffreys]
-
A.
titleHolderFirstChild
Indicates that the subject is the first child of the current or specified title holder.
-
B.
titleHolderChildrenCount
Indicates the number of children associated with the entity that holds a particular title.
-
C.
currentFirstHolder
Indicates that the subject is the entity that currently holds or possesses the object before any subsequent transfer or change of holder.
-
D.
first_holder
Indicates that the subject is the earliest or original holder or possessor of the specified object, title, or right.
-
E.
titleHoldersWere
Indicates that certain entities previously held a specified title or position during a past period.
- 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_69f2247db1108190835c0727c97637c3 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fdb31800508190beec15adb9bbd292 |
completed | May 8, 2026, 9:55 a.m. |
| PD | Predicate disambiguation | batch_69fdb19c381c8190bafb2f565da097f1 |
completed | May 8, 2026, 9:49 a.m. |
| PDg | Predicate description generation | batch_69fdb3172b808190b590d7c5be31ebb7 |
completed | May 8, 2026, 9:55 a.m. |
Created at: April 29, 2026, 7:30 p.m.