Triple
T15321374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bank of New York |
E366298
|
entity |
| Predicate | openedForBusiness |
P990
|
FINISHED |
| Object | 1784 |
—
|
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: 1784 | Statement: [Bank of New York, openedForBusiness, 1784]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openedForBusiness Context triple: [Bank of New York, openedForBusiness, 1784]
-
A.
openingTime
Indicates the time at which a place, service, or event begins operating or becomes accessible.
-
B.
openedForIND
Indicates that an entity has been opened or made available specifically for an Investigational New Drug (IND) application or process.
-
C.
openedBetween
Indicates that an entity was opened during a time interval that falls between two specified temporal bounds.
-
D.
openedForUse
chosen
Indicates that something has been made accessible and available for its intended operation or use.
-
E.
openingHoursCharacteristic
Indicates a relationship that specifies particular attributes or features of an entity’s opening hours, such as patterns, exceptions, or special conditions.
- F. None of above.
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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03dd460288190b5c41f0a0aeee949 |
completed | April 16, 2026, 1:39 a.m. |
| PD | Predicate disambiguation | batch_69deca9659f48190b8661df223ce5078 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:16 a.m.