Triple
T32559475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thunderdome arena |
E832182
|
entity |
| Predicate | audienceTypeInFiction |
P138908
|
FINISHED |
| Object | Bartertown citizens |
—
|
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: Bartertown citizens | Statement: [Thunderdome arena, audienceTypeInFiction, Bartertown citizens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: audienceTypeInFiction Context triple: [Thunderdome arena, audienceTypeInFiction, Bartertown citizens]
-
A.
targetAudienceWithinFiction
chosen
Indicates that the intended audience of a work exists as characters or entities within the fictional world depicted by that work.
-
B.
bodyTypeInFiction
Indicates how a particular body type is portrayed, characterized, or represented within fictional works.
-
C.
fictionalType
Indicates that one entity is a fictional or imaginary type or category of the other entity.
-
D.
typicalStyleInFiction
Indicates the characteristic narrative or artistic style that an entity most commonly exhibits within fictional works.
-
E.
eraOfPopularityInFiction
Indicates the historical time period during which a subject is most commonly or prominently depicted in fictional works.
- 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_69f34926b9848190ace47d2dd0a0de7c |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c604600481908a261d74bdf50bee |
completed | May 3, 2026, 3:50 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2a14b081908162923dfbf0a6f4 |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 1:03 a.m.