Triple
T4945954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aunt Lydia |
E111049
|
entity |
| Predicate | nationalityInBackstory |
P15237
|
FINISHED |
| Object | American |
—
|
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: American | Statement: [Aunt Lydia, nationalityInBackstory, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalityInBackstory Context triple: [Aunt Lydia, nationalityInBackstory, American]
-
A.
nationalityInStory
chosen
Indicates that a character or entity in a narrative is associated with a particular nationality within the context of that story.
-
B.
nationalityInText
Indicates that a person's nationality is mentioned or specified within a given text.
-
C.
nationalityInHumanWorld
Indicates that one entity has the specified national affiliation or citizenship within the context of the human world.
-
D.
originalNationality
Indicates the country or nationality an entity initially belonged to or originated from, before any later changes in citizenship or affiliation.
-
E.
includedNationality
Indicates that one entity’s set of nationalities contains or encompasses the nationality of another entity.
- 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_69bd441721cc819085c7e33fe0876818 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd70aa890c81908e685ec5e88cae1f |
completed | March 20, 2026, 4:07 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3aa1388190b3e0c8ee1ba1e4fa |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:31 p.m.