Triple
T6819906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Parr, 1st Marquess of Northampton |
E156870
|
entity |
| Predicate | hadNoSurvivingIssue |
P40543
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [William Parr, 1st Marquess of Northampton, hadNoSurvivingIssue, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadNoSurvivingIssue Context triple: [William Parr, 1st Marquess of Northampton, hadNoSurvivingIssue, true]
-
A.
deathWithoutIssue
Indicates that a person has died without leaving any surviving descendants or heirs.
-
B.
hadNoSurvivingChildren
chosen
Indicates that the person did not have any children who were alive at the relevant point in time.
-
C.
hadNo
Indicates that one entity completely lacked or did not possess another entity, attribute, or relationship.
-
D.
hasSurvivors
Indicates that one or more entities continue to exist or remain alive after a particular event, condition, or incident.
-
E.
hadNoFatalities
Indicates that the referenced event, incident, or situation resulted in zero deaths.
- 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_69c688298a288190af3f285d57f76bbe |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d359176c8190a34664ba2fcf7ee2 |
completed | March 27, 2026, 6:58 p.m. |
| PD | Predicate disambiguation | batch_69c6d09bb4f881909bf20c188cb3e8e1 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:17 p.m.