Triple
T10168087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OER |
E235256
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | BER |
E71200
|
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: BER | Statement: [OER, relatedTo, BER]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BER Context triple: [OER, relatedTo, BER]
-
A.
BER
BER is a U.S. Department of Energy research program that advances fundamental science on biological systems and environmental processes to address energy and climate challenges.
-
B.
BER
chosen
BER is Berlin Brandenburg Airport, the main international airport serving Germany’s capital region.
-
C.
BER
BER is the ICAO airline designator formerly used by the now-defunct German carrier Air Berlin.
-
D.
Ber
Ber is a traditional Yiddish given name, often associated with Ashkenazi Jewish men and sometimes used as a counterpart to the Hebrew name Dov.
-
E.
BEL
BEL is the ICAO airline designator used to identify Brussels Airlines in international aviation operations.
- 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_69ca84ceafd0819085828600e11bed6b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec6f64a48190883aefce58a65ca6 |
completed | April 2, 2026, 4:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d300ebacb88190850cf2242309b6ba |
completed | April 6, 2026, 12:40 a.m. |
Created at: March 30, 2026, 9:10 p.m.