Triple
T16509878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carrie Ann Morrow |
E401030
|
entity |
| Predicate | hasSiblingOccupation |
P13234
|
FINISHED |
| Object | actress |
—
|
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: actress | Statement: [Carrie Ann Morrow, hasSiblingOccupation, actress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSiblingOccupation Context triple: [Carrie Ann Morrow, hasSiblingOccupation, actress]
-
A.
siblingOccupation
chosen
Indicates that one person has a sibling whose job or profession is the specified occupation.
-
B.
hasChildInSameProfession
Indicates that an individual has at least one child whose profession is the same as their own.
-
C.
hasOccupationRelative
Indicates that one entity has another entity as a relative who holds a particular occupation or job.
-
D.
hasFamilyRelationInWork
Indicates that there exists a family relationship between two entities within the context of a specific work (e.g., book, film, or other creative work).
-
E.
endedOccupationOf
Indicates that one entity brought another entity’s occupation or control of a place or position to an end.
- 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_69d88381f6148190819958a038be990e |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e54f7508190804bbae4c9bc8fe3 |
completed | April 18, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69e296995d388190b88ebe189dce890d |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:14 a.m.