Triple
T5633349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catsmeat Potter-Pirbright |
E147885
|
entity |
| Predicate | romanticInvolvement |
P10693
|
FINISHED |
| Object | often entangled in comic romantic schemes |
—
|
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: often entangled in comic romantic schemes | Statement: [Catsmeat Potter-Pirbright, romanticInvolvement, often entangled in comic romantic schemes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: romanticInvolvement Context triple: [Catsmeat Potter-Pirbright, romanticInvolvement, often entangled in comic romantic schemes]
-
A.
hasRomanticTensionWith
Indicates a mutual or one-sided romantic attraction or unresolved romantic interest existing between two entities.
-
B.
loveInterest
Indicates that one entity is the romantic object of affection or attraction for another entity.
-
C.
romanticArc
chosen
Indicates a developing or ongoing romantic relationship or storyline between the involved entities.
-
D.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
E.
relationshipStatusDuringFilm
Indicates the type or state of a relationship between entities specifically during the time period in which a film takes place or is produced.
- 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_69c00907bc8881909ed760d3ed73ef35 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0225ff3248190b93c9f5887553fd4 |
completed | March 22, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69c01b1f12ec8190b4b9d9ee31cabe19 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:41 p.m.