Triple
T35932472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salem (Days of Our Lives) |
E1039201
|
entity |
| Predicate | hasFictionalSuburbOrArea |
P21117
|
FINISHED |
| Object | West Salem |
—
|
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: West Salem | Statement: [Salem (Days of Our Lives), hasFictionalSuburbOrArea, West Salem]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalSuburbOrArea Context triple: [Salem (Days of Our Lives), hasFictionalSuburbOrArea, West Salem]
-
A.
hasFictionalNearbyTown
Indicates that an entity is associated with a fictional town located in its vicinity or surrounding area.
-
B.
hasFictionalAddressTown
Indicates that an entity is associated with a town that serves as its fictional address location.
-
C.
hasFictionalTownBasedOn
Indicates that a fictional town is modeled on, inspired by, or derived from a specific real-world town or location.
-
D.
hasFictionalTownType
Indicates that a fictional town is classified as being of a particular type or category.
-
E.
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.
- 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_69f76e23e4688190a5369138755138bf |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ffef812da48190b875a7376b24f92d |
completed | May 10, 2026, 2:37 a.m. |
| PD | Predicate disambiguation | batch_69ffedecd580819097851b1473fdd6ed |
completed | May 10, 2026, 2:31 a.m. |
Created at: May 3, 2026, 4:07 p.m.