Triple
T16108070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asia/Bahrain |
E390793
|
entity |
| Predicate | ianaTzIdentifierString |
P6294
|
FINISHED |
| Object | "Asia/Bahrain" |
—
|
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: "Asia/Bahrain" | Statement: [Asia/Bahrain, ianaTzIdentifierString, "Asia/Bahrain"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ianaTzIdentifierString Context triple: [Asia/Bahrain, ianaTzIdentifierString, "Asia/Bahrain"]
-
A.
ianaTimeZoneNameFormat
Indicates how a time-related value is represented or labeled according to the IANA time zone naming convention.
-
B.
ianaTimeZoneId
chosen
Indicates the association between an entity and its time zone as identified by a standard IANA time zone identifier (e.g., "America/New_York").
-
C.
IANATimeZoneIdentifierExample
Indicates that the relationship provides an example of an IANA time zone identifier corresponding to a given time zone or context.
-
D.
javaTimeZoneID
Indicates that an entity is associated with a specific Java time zone identifier (e.g., "America/New_York") used for date and time operations.
-
E.
timeZoneName
Indicates the specific time zone designation (such as its standard name or label) associated with an entity.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e20165aa9c81908c5358cca2b0d0fe |
completed | April 17, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69e1828518c48190a8ef3aaa46a1f639 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5 a.m.