Triple
T25708296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Myrtle |
E644659
|
entity |
| Predicate | romanticRoleType |
P158128
|
FINISHED |
| Object | sentimental lover |
—
|
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: sentimental lover | Statement: [Myrtle, romanticRoleType, sentimental lover]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: romanticRoleType Context triple: [Myrtle, romanticRoleType, sentimental lover]
-
A.
romanceType
chosen
Indicates the specific kind or category of romantic relationship that exists between the related entities.
-
B.
romanticPattern
Indicates a recurring style, tendency, or structure in how romantic relationships or attractions develop or are expressed between entities.
-
C.
romanticArc
Indicates a developing or ongoing romantic relationship or storyline between the involved entities.
-
D.
romanticallyObsessedWith
Indicates a strong, often overwhelming romantic fixation or preoccupation that one entity has toward another.
-
E.
romanticPartnerInSeries
Indicates that one character is portrayed as a romantic partner of another character within the context of a specific series or narrative.
- 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_69e77e83c8ec8190bf52fcdac4838984 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fc1385c4819082eff6432380dd2c |
completed | May 2, 2026, 1:28 p.m. |
| PD | Predicate disambiguation | batch_69f480824a1c81908a8a492eedbc2596 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 9:07 p.m.