Triple
T10907612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nick Miller |
E257611
|
entity |
| Predicate | primarySettingOfStories |
P14490
|
FINISHED |
| Object | Loft in Los Angeles |
—
|
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: Loft in Los Angeles | Statement: [Nick Miller, primarySettingOfStories, Loft in Los Angeles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primarySettingOfStories Context triple: [Nick Miller, primarySettingOfStories, Loft in Los Angeles]
-
A.
primarySettingOf
chosen
Indicates that a location or context serves as the main or principal setting in which an entity (such as a story, event, or activity) takes place.
-
B.
primarySetting
Indicates that one entity serves as the main or central location, context, or environment in which the other entity’s events or activities primarily take place.
-
C.
primarySettingFeature
Indicates that a particular feature is the main or defining characteristic of a setting.
-
D.
primaryContent
Indicates that one entity serves as the main or most important content associated with another entity.
-
E.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
- 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7706756d081908ed29c68d81df688 |
completed | April 9, 2026, 9:24 a.m. |
| PD | Predicate disambiguation | batch_69d70d3d69e08190bb369e9a7927142c |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:22 p.m.