Triple
T15231078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | STS-87 |
E364000
|
entity |
| Predicate | primaryPayload |
P21685
|
FINISHED |
| Object |
USMP-4
USMP-4 was a NASA microgravity research mission module that conducted materials science and fluid physics experiments in space.
|
E1144394
|
NE FINISHED |
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: USMP-4 | Statement: [STS-87, primaryPayload, USMP-4]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: USMP-4 Context triple: [STS-87, primaryPayload, USMP-4]
-
A.
USMP
USMP is a private Peruvian university known formally as the Universidad de San Martín de Porres, offering a wide range of academic programs and professional training.
-
B.
UP-43
UP-43 is the motor vehicle registration code assigned to the Gonda district in the Indian state of Uttar Pradesh.
-
C.
USPMM
USPMM is the port code designating the Portland International Marine Terminal in Portland, Maine, a commercial cargo and container shipping facility.
-
D.
MP 44
MP 44 is a German World War II-era assault rifle, better known as the Sturmgewehr 44, widely regarded as one of the first modern assault rifles.
-
E.
USSF-44
USSF-44 is a classified U.S. Space Force national security mission launched on a Falcon Heavy rocket to deploy military payloads into geostationary orbit.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: USMP-4 Triple: [STS-87, primaryPayload, USMP-4]
Generated description
USMP-4 was a NASA microgravity research mission module that conducted materials science and fluid physics experiments in space.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: USMP-4 Target entity description: USMP-4 was a NASA microgravity research mission module that conducted materials science and fluid physics experiments in space.
-
A.
USMP
USMP is a private Peruvian university known formally as the Universidad de San Martín de Porres, offering a wide range of academic programs and professional training.
-
B.
UP-43
UP-43 is the motor vehicle registration code assigned to the Gonda district in the Indian state of Uttar Pradesh.
-
C.
USPMM
USPMM is the port code designating the Portland International Marine Terminal in Portland, Maine, a commercial cargo and container shipping facility.
-
D.
MP 44
MP 44 is a German World War II-era assault rifle, better known as the Sturmgewehr 44, widely regarded as one of the first modern assault rifles.
-
E.
USSF-44
USSF-44 is a classified U.S. Space Force national security mission launched on a Falcon Heavy rocket to deploy military payloads into geostationary orbit.
- F. None of above. chosen
Provenance (5 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0078e27408190bc13c0ca441f5594 |
completed | April 15, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fedd3beae88190a91af2c9a7def8f8 |
completed | May 9, 2026, 7:07 a.m. |
| NEDg | Description generation | batch_69fede3ef86481908b21bb8c43e490a0 |
completed | May 9, 2026, 7:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fedec501408190831c1cfa38c0db15 |
completed | May 9, 2026, 7:14 a.m. |
Created at: April 10, 2026, 3:12 a.m.