Triple
T25576857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarah Sisko |
E641128
|
entity |
| Predicate | relationshipToBenjaminSisko |
P191555
|
FINISHED |
| Object | biological mother |
—
|
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: biological mother | Statement: [Sarah Sisko, relationshipToBenjaminSisko, biological mother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToBenjaminSisko Context triple: [Sarah Sisko, relationshipToBenjaminSisko, biological mother]
-
A.
relativeTypeTo Leonard McCoy
Indicates the specific family or kinship relationship that an entity has to Leonard McCoy.
-
B.
relationshipToBobBelcher
Indicates the specific familial, social, or professional relationship that one entity has to Bob Belcher.
-
C.
relationshipToJabba
Indicates the specific personal or social connection an entity has to Jabba, such as familial, hierarchical, or associative ties.
-
D.
relationshipToBelcherChildren
Indicates the specific familial or caretaking relationship an entity has to the Belcher children.
-
E.
relationshipToHomer
Indicates the specific familial or social relationship that one entity has to Homer.
- 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_69e75dc281bc819095ec04dc0c3a94d0 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69fce28d6c3081908bf76f5db63ecf68 |
completed | May 7, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69fce12d2f08819082134b5eb3db6a24 |
completed | May 7, 2026, 6:59 p.m. |
| PDg | Predicate description generation | batch_69fce28a74508190aab36551094e8226 |
completed | May 7, 2026, 7:05 p.m. |
Created at: April 21, 2026, 4:01 p.m.