Triple
T13105301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SAM.gov |
E310827
|
entity |
| Predicate | regulatoryBasis |
P125
|
FINISHED |
| Object | FAR |
E1008656
|
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: FAR | Statement: [SAM.gov, regulatoryBasis, FAR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FAR Context triple: [SAM.gov, regulatoryBasis, FAR]
-
A.
FAR
FAR is the acronym for Cuba’s national military organization, the Revolutionary Armed Forces.
-
B.
FAR
FAR is the station code for Faro railway station, a key rail transport hub serving the city of Faro in southern Portugal’s Algarve region.
-
C.
FAR
FAR is the IATA airport code for Hector International Airport serving Fargo, North Dakota.
-
D.
FAR
FAR is a contemporary dance work by British choreographer Wayne McGregor, known for its innovative fusion of technology, complex movement vocabulary, and exploration of the relationship between the body and scientific ideas.
-
E.
FAR
chosen
FAR is the primary set of rules governing the acquisition process and procurement of goods and services by U.S. federal government agencies.
- 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_69d806a872d08190a329806f8ff30df4 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98154c9f48190aeca779d97151759 |
completed | April 10, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e27a325c8190a5c0f1a582340078 |
completed | May 3, 2026, 5:51 a.m. |
Created at: April 9, 2026, 9:05 p.m.