Triple
T9546005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Hughes Gossett |
E230286
|
entity |
| Predicate | hasNotableParentOccupation |
P70430
|
FINISHED |
| Object | daughter of U.S. Chief Justice |
—
|
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: daughter of U.S. Chief Justice | Statement: [Elizabeth Hughes Gossett, hasNotableParentOccupation, daughter of U.S. Chief Justice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableParentOccupation Context triple: [Elizabeth Hughes Gossett, hasNotableParentOccupation, daughter of U.S. Chief Justice]
-
A.
parentOccupation
Indicates that one entity has an occupation which is the job or profession of the other entity’s parent.
-
B.
hasNotableProfessionField
Indicates that an entity’s notable profession or occupation belongs to a particular professional field or domain.
-
C.
hasNotableBearerOccupation
Indicates that an entity is associated with a notable person who holds a specific occupation.
-
D.
hasNotableParent
chosen
Indicates that an entity has a parent who is distinguished, prominent, or otherwise notable.
-
E.
hasChildInSameProfession
Indicates that an individual has at least one child whose profession is the same as their own.
- 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_69ca847c70b8819088a0a0bad64a50d6 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9902fca081909125660ae6336d3f |
completed | April 1, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69ccd58bd21881908b860e3ee469af13 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:02 p.m.