Triple
T9497057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RRQ |
E229034
|
entity |
| Predicate | firstStepIn |
P88947
|
FINISHED |
| Object | TFTP read transfer sequence |
—
|
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: TFTP read transfer sequence | Statement: [RRQ, firstStepIn, TFTP read transfer sequence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstStepIn Context triple: [RRQ, firstStepIn, TFTP read transfer sequence]
-
A.
first
Indicates that one entity precedes all others in an ordered sequence or ranking.
-
B.
firstStageType
Indicates that one entity is the type or category of the first stage or initial phase associated with another entity.
-
C.
firstStageDescription
Indicates that the value provides a textual explanation or summary of the initial or earliest stage in a multi-stage process or sequence.
-
D.
firstStageName
Indicates that one entity is the initial or earliest stage name associated with another entity in a sequence or lifecycle.
-
E.
firstWork
Indicates that the related work is the earliest or initial work created, published, or produced by the entity in question.
- 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_69ca84753660819098e8d416e89e26ae |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd95ecf4148190aa8f4733980166ae |
completed | April 1, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69cca5651a588190a3cfebe249a223e5 |
completed | April 1, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69cca8c6b0f081908334d6c7cf80e03c |
completed | April 1, 2026, 5:10 a.m. |
Created at: March 30, 2026, 7:56 p.m.