Triple
T34329229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Here Come the Brides |
E880955
|
entity |
| Predicate | hasFictionalTownFeature |
P199983
|
FINISHED |
| Object | Bridal Veil Mountain |
—
|
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: Bridal Veil Mountain | Statement: [Here Come the Brides, hasFictionalTownFeature, Bridal Veil Mountain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalTownFeature Context triple: [Here Come the Brides, hasFictionalTownFeature, Bridal Veil Mountain]
-
A.
hasFictionalTownType
Indicates that a fictional town is classified as being of a particular type or category.
-
B.
hasFictionalNearbyTown
Indicates that an entity is associated with a fictional town located in its vicinity or surrounding area.
-
C.
hasFictionalTownBasedOn
Indicates that a fictional town is modeled on, inspired by, or derived from a specific real-world town or location.
-
D.
fictionalTownFeatured
Indicates that a fictional town is prominently depicted or serves as a key setting within a work or medium.
-
E.
hasFictionalAddressTown
Indicates that an entity is associated with a town that serves as its fictional address location.
- F. None of above. chosen
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_69f349ba96a08190b94887bae2d8ee49 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff691f5ae481908597ce245188d31c |
completed | May 9, 2026, 5:04 p.m. |
| PD | Predicate disambiguation | batch_69ff67ceeeb081909fd00cad166c4b6a |
completed | May 9, 2026, 4:58 p.m. |
| PDg | Predicate description generation | batch_69ff691e86d0819099fdb5eca5a95632 |
completed | May 9, 2026, 5:04 p.m. |
Created at: May 1, 2026, 1:58 a.m.