Triple
T31839311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alan Strang |
E812757
|
entity |
| Predicate | hasSexualTensionWith |
P26473
|
FINISHED |
| Object | Jill Mason |
—
|
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: Jill Mason | Statement: [Alan Strang, hasSexualTensionWith, Jill Mason]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSexualTensionWith Context triple: [Alan Strang, hasSexualTensionWith, Jill Mason]
-
A.
hasRomanticTensionWith
chosen
Indicates a mutual or one-sided romantic attraction or unresolved romantic interest existing between two entities.
-
B.
hasFictionalRomanticInterest
Indicates that one entity is portrayed as having a romantic attraction or interest toward another entity within a fictional context.
-
C.
hasRomanticEncounterWith
Indicates that two entities engage in or share a romantic or intimate encounter with each other.
-
D.
loveInterestPortrayedBy
Indicates that a character’s romantic interest is depicted or played by a particular actor or performer.
-
E.
hasAffairWith
Indicates that one entity is engaged in a secret or illicit romantic or sexual relationship with another entity, typically outside a committed partnership.
- 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_69f348ea7ffc8190a2ab43d80277cf59 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69ff2eb19ad88190915fbbe08e8bc84e |
completed | May 9, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69ff2db5dd608190b7b7ba95f19c276c |
completed | May 9, 2026, 12:51 p.m. |
Created at: April 30, 2026, 11:49 p.m.