Triple
T38244033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Endor |
E1013845
|
entity |
| Predicate | hasFictionalLocationRelation |
P21117
|
FINISHED |
| Object | Endor system |
—
|
NE NERFINISHED |
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: Endor system | Statement: [Endor, hasFictionalLocationRelation, Endor system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalLocationRelation Context triple: [Endor, hasFictionalLocationRelation, Endor system]
-
A.
hasFictionalLocation
chosen
Indicates that an entity is associated with, set in, or takes place within a location that exists only in fiction rather than in the real world.
-
B.
hasBranchInFictionalLocation
Indicates that an organization maintains a branch, office, or presence within a fictional or imaginary location.
-
C.
fictionalLocationAssociatedWith
Indicates a relationship where a fictional entity (such as a character, event, or work) is connected to or set in a particular fictional location.
-
D.
hasFictionalGeographicIdentity
Indicates that an entity is associated with a geographic location that is fictional rather than real.
-
E.
connectsFictionalLocations
Indicates a relationship where one fictional location is linked or joined to another fictional location.
- 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_69f76dd7e89c8190b7866bc85aea521b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a00818b20a881909fbf3bb33dcf7029 |
completed | May 10, 2026, 1 p.m. |
| PD | Predicate disambiguation | batch_6a0080f76f588190a933238861243d1a |
completed | May 10, 2026, 12:58 p.m. |
Created at: May 3, 2026, 4:30 p.m.