Triple
T16289082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FHR |
E395469
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | FHR |
E818148
|
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: FHR | Statement: [FHR, shortName, FHR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FHR Context triple: [FHR, shortName, FHR]
-
A.
FHR
chosen
FHR is a German Fraunhofer research institute specializing in high-frequency physics and advanced radar technologies for civilian and defense applications.
-
B.
FHR
FHR is the commonly used abbreviation for the Ice Hockey Federation of Russia, the governing body for ice hockey in Russia.
-
C.
FFR
FFR is the commonly used abbreviation for the French Rugby Federation, the governing body for rugby union in France.
-
D.
FRF
FRF is a NUTS 1 statistical region code designating the French region of Brittany within the European Union’s territorial classification system.
-
E.
FHP
FHP is the state law enforcement agency responsible for highway safety and traffic enforcement across Florida’s roadways.
- 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e249165af881908ce44c4517c93c12 |
completed | April 17, 2026, 2:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001f94ede48190835e8a0c6f5d0f19 |
completed | May 10, 2026, 6:03 a.m. |
Created at: April 10, 2026, 5:05 a.m.