Triple
T37718867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S.T.A.R.S. |
E939528
|
entity |
| Predicate | handlesThreatType |
P188966
|
FINISHED |
| Object | superhuman threats |
—
|
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: superhuman threats | Statement: [S.T.A.R.S., handlesThreatType, superhuman threats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: handlesThreatType Context triple: [S.T.A.R.S., handlesThreatType, superhuman threats]
-
A.
hasThreatType
Indicates that an entity is associated with, or characterized by, a specific type or category of threat.
-
B.
recognizesThreat
Indicates that an entity identifies or acknowledges another entity or situation as a potential danger or source of harm.
-
C.
threatTypeEncountered
Indicates that an entity has come across or experienced a specific type of threat.
-
D.
hasThreats
Indicates that one entity poses or is associated with potential danger, harm, or adverse consequences toward another entity.
-
E.
systemThreatType
Indicates the category or nature of threat that a system poses or is exposed to.
- 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_69f76edc208c8190bc8b9683f75e1024 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaf48ba148190a8bdfd6846ad0540 |
completed | May 6, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69fbadf632ec8190b14991c971258307 |
completed | May 6, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69fbaeef9c488190babb546b962b4fb6 |
completed | May 6, 2026, 9:13 p.m. |
Created at: May 3, 2026, 4:18 p.m.