Triple
T11000316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Special Purpose Dexterous Manipulator |
E259986
|
entity |
| Predicate | hasAlias |
P455
|
FINISHED |
| Object | SPDM |
E259987
|
NE 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: SPDM | Statement: [Special Purpose Dexterous Manipulator, hasAlias, SPDM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SPDM Context triple: [Special Purpose Dexterous Manipulator, hasAlias, SPDM]
-
A.
SPDM
chosen
SPDM (Special Purpose Dexterous Manipulator) is a two-armed robotic system on the International Space Station used for precise maintenance and repair tasks to reduce the need for astronaut spacewalks.
-
B.
SPEM
SPEM (Software & Systems Process Engineering Metamodel) is an OMG standard modeling language used to define, document, and manage software and systems development processes.
-
C.
SDM
SDM refers to a Sub-Divisional Magistrate, a key administrative and executive officer in charge of governance, revenue, and law-and-order functions within a sub-division of a district in India.
-
D.
SDM
SDM is the IATA airport code for Brown Field Municipal Airport, a public airport serving the San Diego, California area.
-
E.
SDM
SDM is the ICAO airline designator used to identify Rossiya Airlines in international aviation operations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d796d5457c819096630246fa5f7076 |
completed | April 9, 2026, 12:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e37486b23081909ad282397c50a913 |
completed | April 18, 2026, 12:09 p.m. |
Created at: April 8, 2026, 9:25 p.m.