Triple
T32212555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ChaSTE |
E822846
|
entity |
| Predicate | aboardLander |
P152699
|
FINISHED |
| Object | Vikram lander |
—
|
NE NERFINISHED |
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: Vikram lander | Statement: [ChaSTE, aboardLander, Vikram lander]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aboardLander Context triple: [ChaSTE, aboardLander, Vikram lander]
-
A.
carriesLander
Indicates that one entity transports or holds a lander as its payload or cargo.
-
B.
associatedLander
chosen
Indicates that there is a relationship or connection between an entity and a specific lander (e.g., a spacecraft or landing module) involved with it.
-
C.
aboardSpacecraft
Indicates that one entity is physically present on or inside a spacecraft as an occupant or passenger.
-
D.
firstSuccessfulLander
Indicates that the subject entity is the earliest one to have successfully landed on the specified target or within the given context.
-
E.
wasLandingSiteForAstronaut
Indicates that a particular location served as the landing site for an astronaut.
- 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_69f3490a3bec819097bc58d4731b9d08 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bb9412e8819091bd6ee4a29257b7 |
completed | May 3, 2026, 3:05 a.m. |
| PD | Predicate disambiguation | batch_69f6b6293188819080d5041ca0adb969 |
completed | May 3, 2026, 2:42 a.m. |
Created at: May 1, 2026, 12:37 a.m.