Triple
T38262968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Deer Park universe |
E1017975
|
entity |
| Predicate | containsFictionalTown |
P203812
|
FINISHED |
| Object | Desert D'Or |
E2263231
|
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: Desert D'Or | Statement: [The Deer Park universe, containsFictionalTown, Desert D'Or]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsFictionalTown Context triple: [The Deer Park universe, containsFictionalTown, Desert D'Or]
-
A.
hasFictionalTownFeature
Indicates that one entity possesses or includes a feature, characteristic, or element associated with a fictional town.
-
B.
hasFictionalTownType
Indicates that a fictional town is classified as being of a particular type or category.
-
C.
hasFictionalNearbyTown
Indicates that an entity is associated with a fictional town located in its vicinity or surrounding area.
-
D.
hasFictionalTownBasedOn
Indicates that a fictional town is modeled on, inspired by, or derived from a specific real-world town or location.
-
E.
hasFictionalAddressTown
Indicates that an entity is associated with a town that serves as its fictional address location.
- F. None of above. chosen
Provenance (5 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_69f76de33e4481909099fa812709bd42 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a020ab9630c8190a55efd5704cc6043 |
completed | May 11, 2026, 4:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a419df4b8dc81908048a392fb5edc0d |
completed | June 28, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_6a020800e2b88190a1a37e710d8c92bf |
completed | May 11, 2026, 4:46 p.m. |
| PDg | Predicate description generation | batch_6a020ab8b33481908e531bb248d740ad |
completed | May 11, 2026, 4:58 p.m. |
Created at: May 3, 2026, 4:30 p.m.