Triple
T9808087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shuttle Remote Manipulator System |
E238201
|
entity |
| Predicate | segmentCount |
P1905
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Shuttle Remote Manipulator System, segmentCount, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: segmentCount Context triple: [Shuttle Remote Manipulator System, segmentCount, 2]
-
A.
sectionCountApproximate
Indicates that the number of sections associated with an entity is known only approximately rather than as an exact count.
-
B.
branchCount
Indicates the number of branches associated with a given entity or structure.
-
C.
maximumNumberOfSegments
Indicates the greatest allowable or observed count of discrete segments into which something can be or is divided.
-
D.
tileCount
Indicates the number of tiles associated with or contained by a given entity or area.
-
E.
hasNumberOfDivisions
chosen
Indicates the relationship that specifies how many divisions or subunits an entity possesses.
- 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_69ca84defac48190abc1148804f184c1 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdab7ddaac8190a5584a5c863fbaa3 |
completed | April 1, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69cd03dd2da881909052fbf29736a773 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:29 p.m.