Triple
T38371881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Kaluuya as Fred Hampton |
E892606
|
entity |
| Predicate | settingLocationDepicted |
P24427
|
FINISHED |
| Object | Chicago, Illinois |
—
|
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, Illinois | Statement: [Daniel Kaluuya as Fred Hampton, settingLocationDepicted, Chicago, Illinois]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingLocationDepicted Context triple: [Daniel Kaluuya as Fred Hampton, settingLocationDepicted, Chicago, Illinois]
-
A.
state of location depicted
Indicates that the predicate specifies the condition or status of a particular place as shown or represented in some medium (e.g., an image, map, or description).
-
B.
location depicted
Indicates that one entity visually represents or shows the place where another entity is situated or occurs.
-
C.
plotLocation
Indicates the relationship between a creative work and the place or setting where its story or events occur.
-
D.
showLocation
Indicates that one entity displays or reveals the position or place of another entity.
-
E.
placeOfDepiction
chosen
Indicates the location or setting where the depicted subject is shown as being situated in the representation.
- 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_69f76e47cb4c8190bdd92cd1db59c0c5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fdb04ed81c8190b8feea90c1c785a6 |
completed | May 8, 2026, 9:43 a.m. |
| PD | Predicate disambiguation | batch_69fda9d6c5148190a63205b6d9b0a1b4 |
completed | May 8, 2026, 9:16 a.m. |
Created at: May 3, 2026, 4:31 p.m.