Triple
T16317564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jefferson D'Arcy |
E396209
|
entity |
| Predicate | relationshipToMarcy |
P122666
|
FINISHED |
| Object | husband |
—
|
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: husband | Statement: [Jefferson D'Arcy, relationshipToMarcy, husband]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToMarcy Context triple: [Jefferson D'Arcy, relationshipToMarcy, husband]
-
A.
relationshipToTracyLord
Indicates the specific type of personal or social relationship an entity has with Tracy Lord.
-
B.
relationshipTypeWithMaryTyrone
Indicates the specific nature or category of the relationship that an entity has with Mary Tyrone.
-
C.
relationshipStatusWithMichael
Indicates the type or state of the relationship that an entity currently has with Michael.
-
D.
relationshipToCarmen
Indicates the specific type of personal or social relationship an entity has with Carmen.
-
E.
relationshipToNicole
Indicates the specific type of relationship or connection that an entity has with Nicole.
- 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e296b31b988190bb1fde36dae11bbd |
completed | April 17, 2026, 8:23 p.m. |
| PD | Predicate disambiguation | batch_69e219fc72c881909d452274e7af8238 |
completed | April 17, 2026, 11:31 a.m. |
| PDg | Predicate description generation | batch_69e21e56e0348190a3d9475360231a70 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:06 a.m.