Triple
T17616196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | STS-130 |
E429088
|
entity |
| Predicate | ISSModuleName |
P128296
|
FINISHED |
| Object | Node 3 (Tranquility) |
—
|
NE NERFINISHED |
How this triple was built (4 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: Node 3 (Tranquility) | Statement: [STS-130, ISSModuleName, Node 3 (Tranquility)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Node 3 (Tranquility) Context triple: [STS-130, ISSModuleName, Node 3 (Tranquility)]
-
A.
Line 3
Line 3 is one of the main lines of the Barcelona Metro system, running through central parts of the city and connecting several key stations and neighborhoods.
-
B.
Line 3
Line 3 is a major line of the Saint Petersburg Metro system, serving as one of the city's primary rapid transit routes.
-
C.
Line 3
Line 3 is one of the main lines of the Paris Métro, running in an east–west direction across the city and serving several central districts.
-
D.
Line 3
Line 3 is a major rapid transit route of the Guangzhou Metro system, known for its high passenger volume and key role in connecting central urban areas with the airport and suburban districts.
-
E.
Line 3
Line 3 is a major north–south route of the Seoul Metropolitan Subway system, connecting key residential and commercial districts across the city and into surrounding areas.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Node 3 (Tranquility) Target entity description: Node 3 (Tranquility) is an International Space Station module that provides life-support systems, crew quarters, and exercise facilities, significantly enhancing the station’s habitability.
-
A.
Line 3
Line 3 is one of the main lines of the Barcelona Metro system, running through central parts of the city and connecting several key stations and neighborhoods.
-
B.
Line 3
Line 3 is a major line of the Saint Petersburg Metro system, serving as one of the city's primary rapid transit routes.
-
C.
Line 3
Line 3 is one of the main lines of the Paris Métro, running in an east–west direction across the city and serving several central districts.
-
D.
Line 3
Line 3 is a major rapid transit route of the Guangzhou Metro system, known for its high passenger volume and key role in connecting central urban areas with the airport and suburban districts.
-
E.
Line 3
Line 3 is a major north–south route of the Seoul Metropolitan Subway system, connecting key residential and commercial districts across the city and into surrounding areas.
- F. None of above. chosen
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ISSModuleName Context triple: [STS-130, ISSModuleName, Node 3 (Tranquility)]
-
A.
commandModuleName
Indicates the name assigned to a specific command module within a system or application.
-
B.
firstISSModule
Indicates that one entity is the first module of the International Space Station relative to another entity.
-
C.
moduleType
Indicates the classification or category of a module in terms of its functional or structural type.
-
D.
issModuleVisited
Indicates that a specific ISS module has been entered or visited by an entity (such as an astronaut or spacecraft) at least once.
-
E.
moduloPatternName
Indicates that an entity is associated with a specific naming pattern used for modulo-based grouping or partitioning.
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46d32991c81909801161b0a416c94 |
completed | April 19, 2026, 5:50 a.m. |
| PD | Predicate disambiguation | batch_69e3cdd7da34819099bc9481c5a79bab |
completed | April 18, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69e3cfaac2b881909e1140339eb1a0dd |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 5:51 a.m.