Triple
T32195900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | chronic lymphocytic leukemia |
E822402
|
entity |
| Predicate | sexPredominance |
P63667
|
FINISHED |
| Object | more common in males |
—
|
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: more common in males | Statement: [chronic lymphocytic leukemia, sexPredominance, more common in males]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sexPredominance Context triple: [chronic lymphocytic leukemia, sexPredominance, more common in males]
-
A.
hasSexPredominance
chosen
Indicates that one sex (male or female) is more commonly or predominantly associated with the given condition, trait, or occurrence than the other.
-
B.
genderRatio
Indicates the proportional relationship between different genders within a given group or population.
-
C.
sexStatus
Indicates whether and how a sexual relationship or sexual activity exists or has occurred between the related entities.
-
D.
sexDifference
Indicates a relationship where two entities differ from each other specifically in terms of biological sex.
-
E.
sexType
Indicates the specific category or type of sexual activity or sexual relationship involved between entities.
- 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_69f3490819cc81909bae1f8ce99423c5 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bb3795fc8190bfcb00d45aa887a1 |
completed | May 3, 2026, 3:04 a.m. |
| PD | Predicate disambiguation | batch_69f6b3aa892481908d29283a074e6722 |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:35 a.m.