Triple
T13529238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shuttle–Mir Program |
E323088
|
entity |
| Predicate | numberOfDockingMissions |
P110716
|
FINISHED |
| Object | 11 |
—
|
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: 11 | Statement: [Shuttle–Mir Program, numberOfDockingMissions, 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfDockingMissions Context triple: [Shuttle–Mir Program, numberOfDockingMissions, 11]
-
A.
numberOfUncrewedMissions
Indicates the total count of missions carried out without any crew on board.
-
B.
launchesCrewedMissions
Indicates that an entity initiates and sends human-crewed space missions into space or to specific destinations.
-
C.
spaceMissionsFlown
Indicates the number or specific instances of space missions that an entity has participated in or carried out.
-
D.
numberOfSuccessfulMissions
Indicates the count of missions that have been completed successfully by the referenced entity or within the specified context.
-
E.
numberOfCrewedLandings
Indicates the count of distinct landing events that involved a crewed (human-occupied) spacecraft.
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafba2c308190873efd15dfe26358 |
completed | April 12, 2026, 2:44 p.m. |
| PD | Predicate disambiguation | batch_69dbae1046c48190b4ee98c6c9cb9d85 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbaecc98cc8190829f5be759c4f1e3 |
completed | April 12, 2026, 2:40 p.m. |
Created at: April 9, 2026, 9:44 p.m.