Triple
T20994815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Kenton |
E517119
|
entity |
| Predicate | relationshipTypeWithStevens |
P142404
|
FINISHED |
| Object | unspoken romantic tension |
—
|
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: unspoken romantic tension | Statement: [Miss Kenton, relationshipTypeWithStevens, unspoken romantic tension]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithStevens Context triple: [Miss Kenton, relationshipTypeWithStevens, unspoken romantic tension]
-
A.
relationshipToUniversity
Indicates the type or nature of a person's or entity's connection or affiliation with a specific university.
-
B.
relationshipToStanley
Indicates the specific type of personal or social relationship an entity has with Stanley.
-
C.
relationshipTypeWithStuPrice
Indicates the specific type or nature of the relationship that an entity has with Stu Price.
-
D.
relationshipToStudents
Indicates the type or nature of connection one entity has with students, such as role, affiliation, or responsibility toward them.
-
E.
relativeTypeOfSteveSloan
Indicates that one entity is a relative of Steve Sloan, specifying a familial relationship to him.
- F. None of above. chosen
Provenance (4 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_69e0b5006e2881909fc2383f841740cc |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc1e75188190a97114238ea0b4f9 |
completed | April 21, 2026, 4:25 a.m. |
| PD | Predicate disambiguation | batch_69e5dbec80708190a49bccab7ff97e7b |
completed | April 20, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69e5e2df1a888190b5b478e76bdf7fdf |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 16, 2026, 1:50 p.m.