Triple
T37798891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Helen Bryce |
E942312
|
entity |
| Predicate | relationshipStatusWithLexLuthor |
P204392
|
FINISHED |
| Object | former fiancée |
—
|
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: former fiancée | Statement: [Dr. Helen Bryce, relationshipStatusWithLexLuthor, former fiancée]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipStatusWithLexLuthor Context triple: [Dr. Helen Bryce, relationshipStatusWithLexLuthor, former fiancée]
-
A.
relationshipToClarkKent
Indicates the specific personal, social, or familial connection that one entity has to Clark Kent.
-
B.
relationshipStatusWithDrEvil
Indicates the type or state of a person's relationship with Dr. Evil.
-
C.
relationshipToJonathanKent
Indicates the specific familial or personal relationship that an entity has to Jonathan Kent.
-
D.
relationshipTypeWithJohnLuther
Indicates the specific nature or category of the relationship an entity has with John Luther.
-
E.
relationshipWithTitans
Indicates a relationship or association that an entity has with one or more Titans, such as alliances, conflicts, or other significant interactions.
- 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_69f76ee6f1f4819091e2cf9c9e6aee19 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1772e48190ba738c6d11b321e2 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:19 p.m.