Triple
T25986720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zero |
E646222
|
entity |
| Predicate | dangerOfExposure |
P136373
|
FINISHED |
| Object | drives humanoids insane upon direct sight |
—
|
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: drives humanoids insane upon direct sight | Statement: [Zero, dangerOfExposure, drives humanoids insane upon direct sight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dangerOfExposure Context triple: [Zero, dangerOfExposure, drives humanoids insane upon direct sight]
-
A.
hasRiskFrom
chosen
Indicates that one entity is exposed to or may suffer potential harm, loss, or adverse effects as a result of another entity.
-
B.
dangerWarning
Indicates that one entity issues or represents a warning about potential danger associated with another entity or situation.
-
C.
routeOfExposure
Indicates the pathway or method by which an agent, substance, or factor comes into contact with or enters an organism or system.
-
D.
dangerousWhen
Indicates that one entity becomes harmful, risky, or unsafe under the conditions or in the presence of another entity or situation.
-
E.
endangerment
Indicates a relationship in which one entity exposes another to potential harm, risk, or danger.
- 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_69e77e881fc08190ba1c8dc7e2a07f97 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f605446ca48190907baef523f13ccf |
completed | May 2, 2026, 2:08 p.m. |
| PD | Predicate disambiguation | batch_69f4a10480748190a2e67bd399fc435d |
completed | May 1, 2026, 12:48 p.m. |
Created at: April 22, 2026, 8:55 a.m.