Triple
T25641778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Shepard |
E642854
|
entity |
| Predicate | firstBoosterLanding |
P82944
|
FINISHED |
| Object | 2015-11-23 |
—
|
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: 2015-11-23 | Statement: [New Shepard, firstBoosterLanding, 2015-11-23]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstBoosterLanding Context triple: [New Shepard, firstBoosterLanding, 2015-11-23]
-
A.
firstLandingAttemptOn
Indicates that an entity makes its initial attempt to land on another entity or location.
-
B.
firstLandingBy
Indicates that one entity is the earliest or initial instance to arrive, land, or touch down at a particular place or target relative to others.
-
C.
firstSuccessfulLander
Indicates that the subject entity is the earliest one to have successfully landed on the specified target or within the given context.
-
D.
firstSoftLandingBy
chosen
Indicates that the subject is the first entity to successfully achieve a soft landing on the object.
-
E.
firstMannedDescent
Indicates that the subject entity is the first to have carried humans in a descent to the object entity (such as a location, surface, or depth).
- 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_69e77e7ce28081908b08d65ee6e5c8be |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69fce7671f108190bf3ebf54339068b5 |
completed | May 7, 2026, 7:26 p.m. |
| PD | Predicate disambiguation | batch_69fce5b5a84c81908ac1b5b9f08d48d0 |
completed | May 7, 2026, 7:19 p.m. |
Created at: April 21, 2026, 5:44 p.m.