Triple
T2200829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aileen Wuornos in Monster |
E50483
|
entity |
| Predicate | hasRomanticPartnerInFiction |
P9994
|
FINISHED |
| Object | Selby Wall in Monster |
—
|
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: Selby Wall in Monster | Statement: [Aileen Wuornos in Monster, hasRomanticPartnerInFiction, Selby Wall in Monster]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRomanticPartnerInFiction Context triple: [Aileen Wuornos in Monster, hasRomanticPartnerInFiction, Selby Wall in Monster]
-
A.
hasSpouseInStory
Indicates that one entity is depicted as the spouse of another within the context of a particular story or narrative.
-
B.
fictionalRelationship
Indicates a relationship that exists only within a fictional or imagined context between entities.
-
C.
hasRomanticTensionWith
Indicates a mutual or one-sided romantic attraction or unresolved romantic interest existing between two entities.
-
D.
spouseOrLover
chosen
Indicates a romantic partnership between two entities, whether formalized as a spouse or existing as a lover.
-
E.
hasMarriagePlot
Indicates that the work’s narrative centrally involves courtship, romantic relationships, or the progression toward marriage as a key plot element.
- 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_69a88b044ab48190add007487680f009 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbfa06bb4819092d7021358846e5f |
completed | March 7, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69abbda706f4819094de73e1d1d1f539 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.