Triple
T34116936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clay County |
E874997
|
entity |
| Predicate | associatedStateInFiction |
P13811
|
FINISHED |
| Object | Georgia |
E14900
|
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: Georgia | Statement: [Clay County, associatedStateInFiction, Georgia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedStateInFiction Context triple: [Clay County, associatedStateInFiction, Georgia]
-
A.
stateInFiction
chosen
Indicates that a particular state or condition exists within a fictional context or narrative world rather than in real-world actuality.
-
B.
relatedToInFiction
Indicates that one entity is connected to another within a fictional context, such as a story, universe, or narrative work.
-
C.
associatedWithCaseInFiction
Indicates that an entity is connected to, involved in, or relevant to a particular case or investigation within a fictional context.
-
D.
associatedWithCountryInFiction
Indicates a fictional relationship in which an entity is linked or connected to a particular country within a fictional context or narrative.
-
E.
associatedWithFictionalSetting
Indicates that an entity has a connection or relevance to a particular fictional setting or universe.
- 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_69f349a9271c81909576994c9ef7b179 |
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_6a36f9afe5e881908366a344c11a1ed2 |
completed | June 20, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:53 a.m.