Triple
T12883677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christmas Town |
E308165
|
entity |
| Predicate | opposedAestheticTo |
P102534
|
FINISHED |
| Object | gothic horror of Halloween Town |
—
|
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: gothic horror of Halloween Town | Statement: [Christmas Town, opposedAestheticTo, gothic horror of Halloween Town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opposedAestheticTo Context triple: [Christmas Town, opposedAestheticTo, gothic horror of Halloween Town]
-
A.
opposedQualityTo
Indicates that one quality stands in direct opposition or contrast to another quality.
-
B.
associatedAesthetic
chosen
Indicates a relationship where one entity is linked to or characterized by a particular aesthetic style, quality, or visual/theme-based sensibility.
-
C.
theoryOpposed
Indicates that one theory stands in opposition to, or conflicts with, another theory.
-
D.
typeOfOpposition
Indicates a relationship where one entity stands in opposition or contrast to another, such as being a rival, adversary, or countering force.
-
E.
opposite
Indicates that one entity is positioned or oriented directly across from, or in a contrary or reverse relation to, another entity.
- 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97c7f91d08190aac2f6419d3ba992 |
completed | April 10, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69d96fa55b888190ab1612e93c41aec4 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:39 p.m.