Triple
T27343697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Falcon 9 first stage booster B1031 |
E684174
|
entity |
| Predicate | firstLandingOutcome |
P198987
|
FINISHED |
| Object | successful |
—
|
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: successful | Statement: [Falcon 9 first stage booster B1031, firstLandingOutcome, successful]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstLandingOutcome Context triple: [Falcon 9 first stage booster B1031, firstLandingOutcome, successful]
-
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
Indicates that the subject is the first entity to successfully achieve a soft landing on the object.
-
E.
firstLandingSite
Indicates the location where an entity initially arrives, lands, or touches down before any subsequent movements or landings.
- 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_69ef1480a76481908684256ddd5bfda3 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69ff1a972bf08190860696ffcd887c0f |
completed | May 9, 2026, 11:29 a.m. |
| PD | Predicate disambiguation | batch_69ff184005d88190bf38283ebc499b28 |
completed | May 9, 2026, 11:19 a.m. |
| PDg | Predicate description generation | batch_69ff1a95b6fc81909331bb03e263b5b9 |
completed | May 9, 2026, 11:29 a.m. |
Created at: April 27, 2026, 11:44 a.m.