Triple
T30393868
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Keen |
E773159
|
entity |
| Predicate | relationshipTypeWith Elizabeth Keen |
P133754
|
FINISHED |
| Object | romantic relationship |
—
|
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: romantic relationship | Statement: [Tom Keen, relationshipTypeWith Elizabeth Keen, romantic relationship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWith Elizabeth Keen Context triple: [Tom Keen, relationshipTypeWith Elizabeth Keen, romantic relationship]
-
A.
relationshipToElizabethKeen
chosen
Indicates the specific familial, personal, or professional relationship that one entity has to Elizabeth Keen.
-
B.
relationshipTypeWithSydneyBristow
Indicates the specific nature or category of the relationship an entity has with Sydney Bristow.
-
C.
relationshipWithKateBeckett
Indicates that there exists a personal or professional relationship involving Kate Beckett and another entity.
-
D.
relationshipToJaneRizzoli
Indicates the specific familial, social, or professional relationship that one entity has to Jane Rizzoli.
-
E.
relationshipTypeWithKatnissEverdeen
Indicates the type or nature of the relationship an entity has with Katniss Everdeen.
- 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_69f2248ef0a48190aa54d4d8ac3e5758 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a02f10505988190be5fd57566a90e0f |
completed | May 12, 2026, 9:21 a.m. |
| PD | Predicate disambiguation | batch_6a02f03a8c1481909e137e270119f7ef |
completed | May 12, 2026, 9:17 a.m. |
Created at: April 29, 2026, 8:02 p.m.