Triple
T10510716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Henry |
E247903
|
entity |
| Predicate | marriageStatusWithPennyMarshall |
P20884
|
FINISHED |
| Object | divorced |
—
|
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: divorced | Statement: [Michael Henry, marriageStatusWithPennyMarshall, divorced]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriageStatusWithPennyMarshall Context triple: [Michael Henry, marriageStatusWithPennyMarshall, divorced]
-
A.
marriageStatusWithMaryPickford
Indicates the marital relationship status that an entity has or had with Mary Pickford.
-
B.
parentsMarriageStatus
Indicates the marital status relationship between an individual’s parents (e.g., married, divorced, separated, never married).
-
C.
hasMarriage
Indicates a marital relationship exists between the two entities, specifying that they are or were legally married to each other.
-
D.
marital status
chosen
Indicates the legal or social state of a person’s marriage-related relationship, such as being single, married, divorced, or widowed.
-
E.
marriedBy
Indicates that one entity is the officiant or authority who performs and formalizes the marriage of another entity.
- 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509b542088190868531f84deaf9e4 |
completed | April 7, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69d4fb919ea08190bcc1193e2014d437 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:27 p.m.