Triple
T16103383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HRT |
E390678
|
entity |
| Predicate | canUseSubstance |
P121933
|
FINISHED |
| Object | estrogen |
—
|
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: estrogen | Statement: [HRT, canUseSubstance, estrogen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canUseSubstance Context triple: [HRT, canUseSubstance, estrogen]
-
A.
acceptsSubstance
Indicates that an entity receives, takes in, or allows the use of a specified substance.
-
B.
usedSubstance
Indicates that an entity has consumed, applied, or otherwise made use of a particular substance.
-
C.
hasAddictiveSubstance
Indicates that an entity contains or involves a substance capable of causing addiction in those who use or consume it.
-
D.
hasSubstance
Indicates that one entity contains, consists of, or is composed of a particular substance or material.
-
E.
associatedWithSubstance
Indicates that one entity has a relevant connection or involvement with a particular substance, such as use, presence, exposure, or composition.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1ff6a4b8881908e8dc186381196d8 |
completed | April 17, 2026, 9:37 a.m. |
| PD | Predicate disambiguation | batch_69e182804208819087f35307cd6e4103 |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e1ff5cd7e481908a29214139a3de2e |
completed | April 17, 2026, 9:37 a.m. |
Created at: April 10, 2026, 5 a.m.