Triple
T2655999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | .rf |
E54610
|
entity |
| Predicate | introducedForUse |
P3018
|
FINISHED |
| Object | 2010 |
—
|
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: 2010 | Statement: [.rf, introducedForUse, 2010]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedForUse Context triple: [.rf, introducedForUse, 2010]
-
A.
introducedFor
chosen
Indicates that one entity was presented or brought to the attention of another entity for a specific purpose or role.
-
B.
firstUsedFor
Indicates that one entity was the earliest or original thing for which another entity was used or applied.
-
C.
introducedDuring
Indicates that one entity was first brought into existence, use, or awareness within the time period, event, or context specified by the other entity.
-
D.
introduced
Indicates that one entity caused another entity to become known, presented, or brought into use for the first time to a person, group, or context.
-
E.
introducedAfter
Indicates that one entity was introduced at a later time or stage than another entity.
- 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_69ab49e028948190b97e01d73548b1d9 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abda0ba2208190ad87763ecbef8c3c |
completed | March 7, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69abd815d06481909535c02b0aba8553 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:53 p.m.