Triple
T7192871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lexus |
E167735
|
entity |
| Predicate | firstFlagshipLaunchYear |
P75670
|
FINISHED |
| Object | 1989 |
—
|
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: 1989 | Statement: [Lexus, firstFlagshipLaunchYear, 1989]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstFlagshipLaunchYear Context triple: [Lexus, firstFlagshipLaunchYear, 1989]
-
A.
firstCrewedTestFlightYear
Indicates the calendar year in which an entity conducted its first test flight involving a human crew.
-
B.
firstOrbitalLaunchAttemptDate
Indicates the calendar date on which an entity made its first attempt to launch a vehicle into orbit.
-
C.
firstOrbiterArrivalYear
Indicates the calendar year in which the first spacecraft entered orbit around a specified celestial body.
-
D.
firstGEOlaunchDate
Indicates the date on which an entity conducted its first launch of a satellite into geostationary Earth orbit (GEO).
-
E.
firstOperationalCrewFlightYear
Indicates the year in which the first operational crewed flight associated with the subject took place.
- 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_69c6888b5248819090499a884ee3ec39 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e9036544819083c70a5d2135ba4b |
completed | March 27, 2026, 8:30 p.m. |
| PD | Predicate disambiguation | batch_69c6e752385c819096fbab55566ee2a8 |
completed | March 27, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69c6e8b5f6508190af28e06a7959d717 |
completed | March 27, 2026, 8:29 p.m. |
Created at: March 27, 2026, 2:50 p.m.