Triple
T36489807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LRCN |
E899022
|
entity |
| Predicate | sequenceModelingBy |
P185595
|
FINISHED |
| Object | recurrent neural network |
—
|
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: recurrent neural network | Statement: [LRCN, sequenceModelingBy, recurrent neural network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sequenceModelingBy Context triple: [LRCN, sequenceModelingBy, recurrent neural network]
-
A.
sequenceNotation
Indicates that one entity specifies the ordered symbolic representation (notation) used to express a sequence associated with another entity.
-
B.
sequenceSetting
Indicates that one event, action, or state occurs in a specific ordered position relative to others within a sequence.
-
C.
sequencingMode
Indicates the specific order or pattern in which related items, events, or operations are arranged or executed.
-
D.
sequenceID
Indicates that an entity is associated with a specific position or identifier within an ordered sequence.
-
E.
sequenceInTerm
Indicates that one element occurs as an ordered part or segment within a larger term or expression.
- 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bccf05bc8190b61fdb2b2a315811 |
completed | May 3, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69f7be9b9ab481908328e0e8d8ac73d4 |
completed | May 3, 2026, 9:31 p.m. |
Created at: May 3, 2026, 4:10 p.m.