Triple
T18912266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raymond Reddington |
E462636
|
entity |
| Predicate | relationshipToElizabethKeen |
P133754
|
FINISHED |
| Object | mysterious protector |
—
|
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: mysterious protector | Statement: [Raymond Reddington, relationshipToElizabethKeen, mysterious protector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToElizabethKeen Context triple: [Raymond Reddington, relationshipToElizabethKeen, mysterious protector]
-
A.
relationshipWithKateBeckett
Indicates that there exists a personal or professional relationship involving Kate Beckett and another entity.
-
B.
relationshipToJaneRizzoli
Indicates the specific familial, social, or professional relationship that one entity has to Jane Rizzoli.
-
C.
relationshipToSelinaMeyer
Indicates the specific type of personal or professional relationship an entity has with Selina Meyer.
-
D.
relationshipTypeWithElizabethLeefolt
Indicates the specific nature or category of relationship an entity has with Elizabeth Leefolt.
-
E.
relationshipTypeWithEleanorLance
Indicates the specific nature or category of relationship an entity has with Eleanor Lance.
- 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_69d8dcfdbbb881909964fa5a75bd0b48 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c6238e288190b30311b5d80beafb |
completed | April 20, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69e4a2e9e6488190ba8df92c8058ed88 |
completed | April 19, 2026, 9:39 a.m. |
| PDg | Predicate description generation | batch_69e4ad8e075c8190ad561edc5e520057 |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, 11:58 a.m.