Triple
T36485159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HTV |
E898915
|
entity |
| Predicate | rendezvousMethod |
P53269
|
FINISHED |
| Object | proximity operations then capture by robotic arm |
—
|
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: proximity operations then capture by robotic arm | Statement: [HTV, rendezvousMethod, proximity operations then capture by robotic arm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rendezvousMethod Context triple: [HTV, rendezvousMethod, proximity operations then capture by robotic arm]
-
A.
rendezvousSystem
Indicates a system or mechanism that coordinates and manages the meeting or docking of two or more entities at a specified place and time.
-
B.
rendezvousTarget
Indicates that one entity is designated as the meeting or rendezvous point for another entity.
-
C.
rendezvousWith
Indicates that two or more entities meet or come together at an agreed place and time, often for a specific purpose.
-
D.
rendezvousType
chosen
Indicates the specific kind or category of meeting or rendezvous that occurs between entities.
-
E.
rendezvousCapability
Indicates the ability of one entity to meet or dock with another entity at a planned place and time.
- 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_69f76e5a0e088190a2b6706aeb41723c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bccf05bc8190b61fdb2b2a315811 |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:10 p.m.