Triple
T30644609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edison incandescent lamps |
E780085
|
entity |
| Predicate | safetyComparedTo |
P60758
|
FINISHED |
| Object | safer than open-flame gas lighting |
—
|
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: safer than open-flame gas lighting | Statement: [Edison incandescent lamps, safetyComparedTo, safer than open-flame gas lighting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyComparedTo Context triple: [Edison incandescent lamps, safetyComparedTo, safer than open-flame gas lighting]
-
A.
safetyRationale
Indicates the reasoning or justification provided to explain how and why something is considered safe or made safe.
-
B.
safetyBenefit
chosen
Indicates that one entity provides, contributes to, or results in an improvement in the safety or risk reduction experienced by another entity.
-
C.
safetyComparedToRoads
Indicates how the safety level of something compares relative to that of roads.
-
D.
safety
Indicates that an entity provides, ensures, or is associated with protection from harm, danger, or risk for another entity or within a given context.
-
E.
safetyCategory
Indicates the classification of something according to its level or type of safety.
- 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_69f224a50ebc81909b961a94c7f66b12 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6b49436b0819094e21603054d05d4 |
completed | May 3, 2026, 2:36 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a7bdb481908d16a32f49e38c2c |
completed | May 3, 2026, 2:32 a.m. |
Created at: April 29, 2026, 8:29 p.m.