Triple
T18375103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nasiriyah Teaching Hospital |
E446291
|
entity |
| Predicate | locatedInTimeZone |
P109
|
FINISHED |
| Object | Asia/Baghdad |
—
|
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: Asia/Baghdad | Statement: [Nasiriyah Teaching Hospital, locatedInTimeZone, Asia/Baghdad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asia/Baghdad Context triple: [Nasiriyah Teaching Hospital, locatedInTimeZone, Asia/Baghdad]
-
A.
Asia/Baghdad
chosen
Asia/Baghdad is the IANA time zone identifier representing the local time for Baghdad, Iraq.
-
B.
Asia/Damascus
Asia/Damascus is the IANA time zone identifier representing the local civil time observed in Damascus, Syria.
-
C.
Asia/Kuwait
Asia/Kuwait is the time zone corresponding to Kuwait, used for standard timekeeping in that country and some associated regions.
-
D.
Asia/Amman
Asia/Amman is the time zone used in Jordan’s capital city, Amman, representing the country’s standard local time.
-
E.
Asia/Qatar
Asia/Qatar is the IANA time zone identifier representing the standard time observed throughout the country of Qatar in Western Asia.
- 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_69d8b9f370b88190b1e5081c2c238e7f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e51757a75c8190814db973ae1a86cd |
completed | April 19, 2026, 5:56 p.m. |
Created at: April 10, 2026, 10:45 a.m.