Triple
T28431874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amy Forrest-Rhodes |
E715153
|
entity |
| Predicate | spouseRoleInNotableWork |
P161452
|
FINISHED |
| Object | Clarence Odbody, the angel |
—
|
NE NERFINISHED |
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: Clarence Odbody, the angel | Statement: [Amy Forrest-Rhodes, spouseRoleInNotableWork, Clarence Odbody, the angel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseRoleInNotableWork Context triple: [Amy Forrest-Rhodes, spouseRoleInNotableWork, Clarence Odbody, the angel]
-
A.
spouseNotableWorkField
Indicates that the notable work or professional field associated with a person’s spouse is being specified.
-
B.
spouse notableWork
chosen
Indicates that a person's spouse is significantly associated with a particular notable work.
-
C.
spouseNotableFor
Indicates that a person's spouse is recognized or distinguished for a particular achievement, role, or characteristic.
-
D.
spouseOfRole
Indicates that one role is the spouse (husband, wife, or equivalent marital partner) of another role.
-
E.
spouseNotableWorkLanguage
Indicates that the notable work of a person's spouse is expressed or created in a particular language.
- 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_69efd6b253888190b3c7222ed6a403a8 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f73223675481908c1bc3208c0f5284 |
completed | May 3, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69f7317690108190b3aae2cd2e1d069e |
completed | May 3, 2026, 11:28 a.m. |
Created at: April 28, 2026, 1:40 a.m.