Triple
T34262369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rose Brice |
E879067
|
entity |
| Predicate | primarySettingOfCharacter |
P90820
|
FINISHED |
| Object | New York City |
E40
|
NE 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: New York City | Statement: [Rose Brice, primarySettingOfCharacter, New York City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primarySettingOfCharacter Context triple: [Rose Brice, primarySettingOfCharacter, New York City]
-
A.
primarySettingOf
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.
characterSetting
chosen
Indicates that a character is associated with, appears in, or is situated within a particular setting or environment.
-
C.
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.
-
D.
primaryCharacteristics
Indicates the main defining traits or features that most fundamentally characterize an entity.
-
E.
primarySettingFeature
Indicates that a particular feature is the main or defining characteristic of a setting.
- F. None of above.
Provenance (4 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_69f349b421cc8190b4b4655e1d612548 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a36d5ce7a6481908fae2bbc3356df57 |
completed | June 20, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_6a0379fbe4a08190bfe65ebd141164e9 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:56 a.m.