Triple
T29015964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thai Duong |
E737306
|
entity |
| Predicate | typeOfResearcher |
P91022
|
FINISHED |
| Object | applied security researcher |
—
|
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: applied security researcher | Statement: [Thai Duong, typeOfResearcher, applied security researcher]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfResearcher Context triple: [Thai Duong, typeOfResearcher, applied security researcher]
-
A.
hasResearcherType
chosen
Indicates that an entity is associated with a researcher characterized by a specific type or category of research role.
-
B.
roleInResearch
Indicates that an entity participates in a research activity with a specified function, position, or responsibility within that research.
-
C.
researchUser
Indicates that an entity conducts research on, studies, or investigates a particular user.
-
D.
hasResearcher
Indicates that an entity is associated with or linked to a specific researcher responsible for work, study, or investigation related to it.
-
E.
typeOfScientist
Indicates that one entity is a scientist and the other specifies the kind or specialization of that scientist.
- 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_69f077ee19f881909af48f9cab00a2e5 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fed357b2b4819084c709056a54461f |
completed | May 9, 2026, 6:25 a.m. |
| PD | Predicate disambiguation | batch_69fed103d9cc81909b11619745110c61 |
completed | May 9, 2026, 6:15 a.m. |
Created at: April 28, 2026, 9:45 a.m.