Triple
T24925134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin Gesundbrunnen station |
E618832
|
entity |
| Predicate | IBNR |
P157240
|
FINISHED |
| Object | 8010406 |
—
|
LITERAL 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: 8010406 | Statement: [Berlin Gesundbrunnen station, IBNR, 8010406]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: IBNR Context triple: [Berlin Gesundbrunnen station, IBNR, 8010406]
-
A.
insuranceAccrualRate
Indicates the rate at which insurance-related amounts (such as premiums, costs, or liabilities) accumulate over a specified period.
-
B.
indemnityBasis
Indicates that one party’s obligation to compensate another for loss, damage, or liability is determined according to a specified indemnification standard or method.
-
C.
inForceAtTimeOfIssue
Indicates that the relationship or condition was in effect at the specific time when the associated item or agreement was issued.
-
D.
insurance
Indicates a relationship where one party provides financial protection or coverage to another against specified risks or losses, typically in exchange for payment.
-
E.
typeOfInsurer
Indicates the specific category or classification of an insurer in relation to an insurance policy or coverage.
- F. None of above. chosen
Provenance (4 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_69e2fab9edd88190b86004a78a28bc20 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f423afd1ec8190a7660bc5174f49db |
completed | May 1, 2026, 3:53 a.m. |
| PD | Predicate disambiguation | batch_69f4210130d08190ae30b7943f7a0bbc |
completed | May 1, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f423637bec8190a1701421ac86a3b7 |
completed | May 1, 2026, 3:52 a.m. |
Created at: April 18, 2026, 5:29 a.m.