Triple
T15217780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carol W. Greider |
E363682
|
entity |
| Predicate | hasResearchFocusOn |
P934
|
FINISHED |
| Object | telomere length regulation |
—
|
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: telomere length regulation | Statement: [Carol W. Greider, hasResearchFocusOn, telomere length regulation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasResearchFocusOn Context triple: [Carol W. Greider, hasResearchFocusOn, telomere length regulation]
-
A.
hasScientificInterestIn
Indicates that one entity holds a scientific curiosity, concern, or research focus directed toward another entity.
-
B.
hasResearchArea
chosen
Indicates that an entity (such as a person, project, or organization) is associated with or focused on a particular field or area of research.
-
C.
usesResearchSubject
Indicates that one entity employs or utilizes another entity as a research subject in a study or investigation.
-
D.
conductsResearchAt
Indicates that a subject carries out research activities at a specified institution, organization, or location.
-
E.
hasResearcher
Indicates that an entity is associated with or linked to a specific researcher responsible for work, study, or investigation related to it.
- 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0076f90c481909989befe031a2cae |
completed | April 15, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69deca8479188190b2e5d3bc708d7d07 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:11 a.m.