Triple
T1979776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USSF-44 |
E42997
|
entity |
| Predicate | payload |
P12202
|
FINISHED |
| Object |
TETRA-1
TETRA-1 is a small experimental U.S. military satellite developed for the U.S. Space Force to test and demonstrate prototype space technologies in geosynchronous orbit.
|
E221847
|
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: TETRA-1 | Statement: [USSF-44, payload, TETRA-1]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TETRA-1 Context triple: [USSF-44, payload, TETRA-1]
-
A.
Tetritsqaro
Tetritsqaro is a town in southeastern Georgia that serves as a local administrative and transportation center within the Kvemo Kartli region.
-
B.
TR-1A
The TR-1A is a high-altitude tactical reconnaissance aircraft developed from the Lockheed U-2, optimized for battlefield surveillance and intelligence-gathering missions.
-
C.
tetri
The tetri is the fractional monetary unit of Georgia, used as a subdivision of the Georgian lari.
-
D.
Tekrad
Tekrad was the original name of Tektronix, an American company known for its pioneering electronic test and measurement equipment.
-
E.
TET
TET is a Ukrainian television channel known for broadcasting entertainment, comedy, and family-oriented programming.
- 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: TETRA-1 Triple: [USSF-44, payload, TETRA-1]
Generated description
TETRA-1 is a small experimental U.S. military satellite developed for the U.S. Space Force to test and demonstrate prototype space technologies in geosynchronous orbit.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TETRA-1 Target entity description: TETRA-1 is a small experimental U.S. military satellite developed for the U.S. Space Force to test and demonstrate prototype space technologies in geosynchronous orbit.
-
A.
Tetritsqaro
Tetritsqaro is a town in southeastern Georgia that serves as a local administrative and transportation center within the Kvemo Kartli region.
-
B.
TR-1A
The TR-1A is a high-altitude tactical reconnaissance aircraft developed from the Lockheed U-2, optimized for battlefield surveillance and intelligence-gathering missions.
-
C.
tetri
The tetri is the fractional monetary unit of Georgia, used as a subdivision of the Georgian lari.
-
D.
Tekrad
Tekrad was the original name of Tektronix, an American company known for its pioneering electronic test and measurement equipment.
-
E.
TET
TET is a Ukrainian television channel known for broadcasting entertainment, comedy, and family-oriented programming.
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb7c87bc081908ed179d1ca94fa3b |
completed | March 7, 2026, 5:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae032bc30c8190a136a634580571d9 |
completed | March 8, 2026, 11:15 p.m. |
| NEDg | Description generation | batch_69ae039a7c948190b8b4b4c2045007d3 |
completed | March 8, 2026, 11:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae042728f48190850848116a371794 |
completed | March 8, 2026, 11:20 p.m. |
Created at: March 4, 2026, 7:36 p.m.