Triple
T25542803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zulaykha |
E640215
|
entity |
| Predicate | relationshipToYusuf |
P190650
|
FINISHED |
| Object | initially a would-be seducer |
—
|
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: initially a would-be seducer | Statement: [Zulaykha, relationshipToYusuf, initially a would-be seducer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToYusuf Context triple: [Zulaykha, relationshipToYusuf, initially a would-be seducer]
-
A.
relationToUthman
Indicates the type of relationship or connection an entity has to Uthman.
-
B.
associatedPersonRelationToMuhammad
Indicates the specific type of relationship or connection a person has to Muhammad.
-
C.
relationToKhalidIbnAlWalid
Indicates a relationship or association that an entity has with Khalid ibn al-Walid.
-
D.
relationshipToAmir
Indicates that one entity has a specified personal, social, or familial relationship to the person Amir.
-
E.
relationshipToParents
Indicates the type or nature of a person's familial relationship to their parents.
- 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_69e75dbfff7081909b0aa779d48321d2 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69fcce2cf9188190b3f65b362203a6a3 |
completed | May 7, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69fcccee6240819084680887731ff64b |
completed | May 7, 2026, 5:33 p.m. |
| PDg | Predicate description generation | batch_69fccdd2d84481909a7ce22407def9c7 |
completed | May 7, 2026, 5:37 p.m. |
Created at: April 21, 2026, 3:26 p.m.