Triple
T35116409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flora Cranley |
E1013449
|
entity |
| Predicate | fictionalPartner |
P34570
|
FINISHED |
| Object | Dr. Jack Griffin |
—
|
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: Dr. Jack Griffin | Statement: [Flora Cranley, fictionalPartner, Dr. Jack Griffin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalPartner Context triple: [Flora Cranley, fictionalPartner, Dr. Jack Griffin]
-
A.
romanticPartnerInSeries
Indicates that one character is portrayed as a romantic partner of another character within the context of a specific series or narrative.
-
B.
romanticPartnerInSpinOff
Indicates that two characters are depicted as romantic partners specifically within a spin-off work, rather than (or in addition to) the original series.
-
C.
fictionalRelationship
chosen
Indicates a relationship that exists only within a fictional or imagined context between entities.
-
D.
hasFictionalRomanticInterest
Indicates that one entity is portrayed as having a romantic attraction or interest toward another entity within a fictional context.
-
E.
romanticPartnerPortrayedBy
Indicates that one entity is depicted or portrayed as the romantic partner of another entity in some work or context.
- 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_69f76dd659d08190bcdc00d37caafb62 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fee25dbca481909e6f1c255122b3a8 |
completed | May 9, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69fee1c8915c8190b08b63e42881f1a9 |
completed | May 9, 2026, 7:27 a.m. |
Created at: May 3, 2026, 4:01 p.m.