Triple
T15438963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Graham Hill |
E369847
|
entity |
| Predicate | team |
P3756
|
FINISHED |
| Object | BRM |
E601550
|
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: BRM | Statement: [Graham Hill, team, BRM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BRM Context triple: [Graham Hill, team, BRM]
-
A.
BRM
chosen
BRM (British Racing Motors) was a British Formula One constructor and team known for competing in the World Championship from the 1950s to the 1970s and winning the 1962 Constructors' title.
-
B.
BRM
BRM is the port code for the Port of Broome, a regional deep-water port in Broome, Western Australia, serving shipping, offshore industry, and tourism activities.
-
C.
BRM
BRM is the National Rail station code for Barmouth railway station in Gwynedd, Wales.
-
D.
YBRM
YBRM is the ICAO airport code for Broome International Airport in Western Australia, a regional hub serving the coastal town of Broome.
-
E.
BNRM
BNRM is the National Library of the Kingdom of Morocco, serving as the country’s main institution for preserving and providing access to its written and documentary heritage.
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03eddf258819082679970b7d2b6af |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff21a7d44481909a26b5cc331a3259 |
completed | May 9, 2026, 11:59 a.m. |
Created at: April 10, 2026, 3:21 a.m.