Triple
T38655418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nina H. Fefferman |
E939877
|
entity |
| Predicate | usedCaseStudy |
P2398
|
FINISHED |
| Object | World of Warcraft Corrupted Blood incident |
—
|
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: World of Warcraft Corrupted Blood incident | Statement: [Nina H. Fefferman, usedCaseStudy, World of Warcraft Corrupted Blood incident]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedCaseStudy Context triple: [Nina H. Fefferman, usedCaseStudy, World of Warcraft Corrupted Blood incident]
-
A.
hasCaseStudy
chosen
Indicates that one entity is documented, illustrated, or analyzed by a specific case study associated with it.
-
B.
usesCase
Indicates that one entity employs, applies, or makes practical use of another entity for a particular purpose or function.
-
C.
caseStudyNumber
Indicates the identifying number assigned to a specific case study within a collection or series.
-
D.
usedInPractice
Indicates that something is actually applied or implemented in real-world practice rather than just being theoretical or proposed.
-
E.
usedInCase
Indicates that something (such as an item, method, or piece of information) is employed or applied within a particular case or instance.
- 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_69f76ede49648190a48bfe47032a05a3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:33 p.m.