Triple
T35623781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nancy Walker as Mildred |
E1029389
|
entity |
| Predicate | portrayedByInCountry |
P1507
|
FINISHED |
| Object | Nancy Walker in the United States |
—
|
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: Nancy Walker in the United States | Statement: [Nancy Walker as Mildred, portrayedByInCountry, Nancy Walker in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedByInCountry Context triple: [Nancy Walker as Mildred, portrayedByInCountry, Nancy Walker in the United States]
-
A.
portrayedByCountryOfOrigin
Indicates that an entity is depicted or represented by something originating from a specified country.
-
B.
portrayedByCountryOfCitizenship
Indicates that the subject is depicted or represented by an individual whose country of citizenship is the specified country.
-
C.
portrayedBy
chosen
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
-
D.
portrayedByBirthPlace
Indicates that the person who portrays a role or character was born in a specified place.
-
E.
portrayedByAlsoKnownFor
Indicates that an entity is portrayed by a person who is also notably known for another specific role or work.
- 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_69f76e0709408190bbe322bf1707ef6b |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff5285ed74819097e6e2a9084a079a |
completed | May 9, 2026, 3:28 p.m. |
| PD | Predicate disambiguation | batch_69ff51fbe28881908ac8417dff9db81a |
completed | May 9, 2026, 3:25 p.m. |
Created at: May 3, 2026, 4:05 p.m.