Triple
T31259499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dorcas Malvin |
E797078
|
entity |
| Predicate | relationshipToRogerMalvin |
P207387
|
FINISHED |
| Object | daughter |
—
|
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: daughter | Statement: [Dorcas Malvin, relationshipToRogerMalvin, daughter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToRogerMalvin Context triple: [Dorcas Malvin, relationshipToRogerMalvin, daughter]
-
A.
relationshipTypeWithMarvin
Indicates the specific nature or category of the relationship an entity has with Marvin.
-
B.
relationshipTypeWithSamMalone
Indicates the specific nature or category of relationship that an entity has with Sam Malone.
-
C.
relationshipToTheDude
Indicates the specific type of personal or social relationship that one entity has to the individual referred to as "the Dude."
-
D.
relationshipTypeWithRogerDeBris
Indicates the specific nature or category of relationship that an entity has with Roger De Bris.
-
E.
relationshipToMalcolm
Indicates the nature or type of relationship an entity has with Malcolm.
- 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_69f224dd5fdc81908a4cd24917b67668 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e5174c8190a0bdde7e381b7624 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 29, 2026, 9:12 p.m.