Triple
T19961116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Express InterCity Premium |
E479815
|
entity |
| Predicate | brandNameAbbreviation |
P36276
|
FINISHED |
| Object | EIP |
—
|
NE NERFINISHED |
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: EIP | Statement: [Express InterCity Premium, brandNameAbbreviation, EIP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: EIP Context triple: [Express InterCity Premium, brandNameAbbreviation, EIP]
-
A.
EIP
chosen
EIP is a category of high-speed intercity passenger trains operated in Poland by the national rail company PKP Intercity.
-
B.
EIP
EIP is the abbreviation for Extension and International Programs, an academic unit that oversees continuing education and global learning initiatives.
-
C.
EIT
EIT is a telecommunications investment company based in the United Arab Emirates that holds and manages international telecom assets.
-
D.
EIT
EIT is a European Union body that fosters innovation, entrepreneurship, and education by integrating business, research, and higher education institutions across Europe.
-
E.
ePIC
ePIC is an international consortium that provides and promotes persistent identifier services to ensure long-term, reliable access to digital research data and resources.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65af4520c81909986a47289ba801e |
completed | April 20, 2026, 4:57 p.m. |
Created at: April 10, 2026, 1:54 p.m.