Triple
T7918867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FGB Zarya |
E183893
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | FGB |
E696970
|
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: FGB | Statement: [FGB Zarya, alsoKnownAs, FGB]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FGB Context triple: [FGB Zarya, alsoKnownAs, FGB]
-
A.
FGB
chosen
FGB, better known as Zarya, is the first module of the International Space Station, providing initial power and propulsion functions.
-
B.
FGN
FGN is the acronym commonly used to refer to the federal-level governing authority of the Federal Republic of Nigeria.
-
C.
FGZ
FGZ is the FAA location identifier assigned to Sabre Army Heliport, a U.S. Army helicopter facility.
-
D.
FGP
FGP is the stock ticker symbol for FirstGroup, a leading UK-based transport operator running bus and rail services in the United Kingdom and North America.
-
E.
FGS
FGS is a high-precision optical instrument used on space telescopes to maintain accurate pointing and stabilization during observations.
- 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_69ca828efbe48190bd48482650182e79 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a8fbbb48190b50def4941761a31 |
completed | March 31, 2026, 3:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc563cb0a081909ed43ff45a8a1fa0 |
completed | March 31, 2026, 11:18 p.m. |
Created at: March 30, 2026, 5:05 p.m.