Triple
T28212048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Garner as King Marchand |
E711197
|
entity |
| Predicate | characterOriginCity |
P86009
|
FINISHED |
| Object | Chicago |
—
|
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: Chicago | Statement: [James Garner as King Marchand, characterOriginCity, Chicago]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterOriginCity Context triple: [James Garner as King Marchand, characterOriginCity, Chicago]
-
A.
cityOfFictionalOrigin
chosen
Indicates the city from which a fictional character, entity, or work is described as originating within its narrative or fictional universe.
-
B.
cityOfOriginal
Indicates the city from which something or someone originally comes or was first created or established.
-
C.
countyOfOrigin
Indicates the county from which an entity originally comes or was first produced.
-
D.
characterOrigin
Indicates the source, background, or initial context from which a character originates.
-
E.
homeTownInSeries
Indicates that a character’s hometown is located within a particular fictional series or narrative universe.
- 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_69efb51cb5288190818c1f63a266af11 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69fb3425666081908916fcbf3b5dd907 |
completed | May 6, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69fb2f5f3164819099429c2cc3d24e01 |
completed | May 6, 2026, 12:09 p.m. |
Created at: April 27, 2026, 10:40 p.m.