Triple
T1070702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boeing 767 |
E23320
|
entity |
| Predicate | introducedDate |
P3297
|
FINISHED |
| Object | 1982-09-08 |
—
|
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: 1982-09-08 | Statement: [Boeing 767, introducedDate, 1982-09-08]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedDate Context triple: [Boeing 767, introducedDate, 1982-09-08]
-
A.
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.
-
B.
introducedInYear
chosen
Indicates the year in which something was first introduced, launched, or made available.
-
C.
introducedFor
Indicates that one entity was presented or brought to the attention of another entity for a specific purpose or role.
-
D.
introducedAfter
Indicates that one entity was introduced at a later time or stage than another entity.
-
E.
firstUsedOn
Indicates the date, time, or context in which something was initially applied, activated, or put into use on a particular object or 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_69a493ee1f908190992b5f0d1b04459b |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b92848148190ba8795cb8d0a1d0a |
completed | March 1, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69a4b73844708190a16c9e9824ca2fb6 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.