Triple
T37382814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L’Hôpital’s rule for indeterminate limits |
E928482
|
entity |
| Predicate | isOftenMisusedBy |
P188018
|
FINISHED |
| Object | applying when hypotheses fail |
—
|
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: applying when hypotheses fail | Statement: [L’Hôpital’s rule for indeterminate limits, isOftenMisusedBy, applying when hypotheses fail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOftenMisusedBy Context triple: [L’Hôpital’s rule for indeterminate limits, isOftenMisusedBy, applying when hypotheses fail]
-
A.
isMoreFrequentlyUsedThan
Indicates that one entity is used or occurs with greater frequency than another entity.
-
B.
frequentlyUsedBy
Indicates that something is regularly or commonly utilized by a particular entity.
-
C.
oftenUse
Indicates that one entity frequently or regularly uses, employs, or utilizes another entity.
-
D.
riskIfMisused
Indicates that the subject has the potential to cause harm, danger, or negative consequences if it is used improperly or irresponsibly.
-
E.
isOftenResultOf
Indicates that one situation, event, or condition frequently occurs as a consequence or outcome of another.
- 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_69f76eb9e66881908534cf22d04c3b5a |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb9e1845e881908d19158440cf3b87 |
completed | May 6, 2026, 8:01 p.m. |
| PD | Predicate disambiguation | batch_69fb8d08d6988190a00794ac26078348 |
completed | May 6, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69fb9e173f348190b7ab5935e4dca039 |
completed | May 6, 2026, 8:01 p.m. |
Created at: May 3, 2026, 4:16 p.m.