Triple
T26718865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Captain Victoria Gates |
E673643
|
entity |
| Predicate | relationshipToKateBeckett |
P108892
|
FINISHED |
| Object | commanding officer |
—
|
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: commanding officer | Statement: [Captain Victoria Gates, relationshipToKateBeckett, commanding officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToKateBeckett Context triple: [Captain Victoria Gates, relationshipToKateBeckett, commanding officer]
-
A.
relationshipWithKateBeckett
chosen
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.
relationshipToRichardCastle
Indicates the specific personal or professional relationship that one entity has to Richard Castle.
-
D.
relationshipToShawnSpencer
Indicates the specific type of personal or social relationship an entity has with Shawn Spencer.
-
E.
relationshipTypeWithSydneyBristow
Indicates the specific nature or category of the relationship an entity has with Sydney Bristow.
- 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_69eecda481d08190aea69f2f7c745f56 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69febce5877c8190a5e000ef5331ec88 |
completed | May 9, 2026, 4:49 a.m. |
| PD | Predicate disambiguation | batch_69febad1cd588190abc7686bcb39a371 |
completed | May 9, 2026, 4:40 a.m. |
Created at: April 27, 2026, 3:39 a.m.