Triple
T28880706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GW170814 |
E732408
|
entity |
| Predicate | hasFalseAlarmRate |
P166048
|
FINISHED |
| Object | less than 1 in 27,000 years |
—
|
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: less than 1 in 27,000 years | Statement: [GW170814, hasFalseAlarmRate, less than 1 in 27,000 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFalseAlarmRate Context triple: [GW170814, hasFalseAlarmRate, less than 1 in 27,000 years]
-
A.
falseAlarmProbability
chosen
Indicates the likelihood that an event or signal identified as significant is actually a false alarm rather than a true occurrence.
-
B.
hasErrorRate
Indicates the proportion or frequency at which errors occur in a given process, system, or measurement.
-
C.
childFalseMatchRate
Indicates the proportion of child-related matches that are incorrectly identified as matches (i.e., the false positive rate for child matches).
-
D.
hasFailureProbability
Indicates that an entity is associated with a likelihood or chance that it will fail within a given context or conditions.
-
E.
errorRate
Indicates the proportion or frequency of incorrect outcomes or failures relative to the total number of attempts or operations.
- 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_69f05b06807c81909b4bbd4c20403a2b |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f73ae120bc8190bff94d38d7a7a00d |
completed | May 3, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69f73a38d0848190aa5139144b8561c6 |
completed | May 3, 2026, 12:06 p.m. |
Created at: April 28, 2026, 7:43 a.m.