Triple
T32635951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zinda Rood |
E834343
|
entity |
| Predicate | subjectSonOfBiographee |
P109681
|
FINISHED |
| Object | Javid Iqbal |
—
|
NE NERFINISHED |
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: Javid Iqbal | Statement: [Zinda Rood, subjectSonOfBiographee, Javid Iqbal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectSonOfBiographee Context triple: [Zinda Rood, subjectSonOfBiographee, Javid Iqbal]
-
A.
hasBiographicalSubjectRelationshipWith
Indicates that there exists a biographical relationship or connection between two entities, where one is the subject of biographical information in relation to the other.
-
B.
hasBiographicalRelation
Indicates a relationship where one entity has a biographical connection to another, such as being the subject, author, or source of biographical information.
-
C.
biographerRelationToSubject
Indicates that one entity is the biographer who has written about the life or experiences of the other entity, who is the subject of that biography.
-
D.
isBiographerOf
Indicates that one person has written a biography about another person.
-
E.
listedAsSonOf
chosen
Indicates that one entity is recorded or designated as the son (male child) of another entity.
- F. None of above.
Provenance (3 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_69f3492dc2308190a88c6e30a3f3f576 |
completed | April 30, 2026, 12:21 p.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. |
Created at: May 1, 2026, 1:07 a.m.