Triple
T32976303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nureddin al-Atassi |
E843670
|
entity |
| Predicate | officeStartTime (President of Syria) |
P199640
|
FINISHED |
| Object | 1966-02-25 |
—
|
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: 1966-02-25 | Statement: [Nureddin al-Atassi, officeStartTime (President of Syria), 1966-02-25]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeStartTime (President of Syria) Context triple: [Nureddin al-Atassi, officeStartTime (President of Syria), 1966-02-25]
-
A.
officeStartTime (President of Iraq)
Indicates the date and time at which the President of Iraq officially begins their term in office.
-
B.
officeStartTime (President of the Republic of China)
Indicates the date and time at which a person begins their term in office as President of the Republic of China.
-
C.
officeStartTime (President of India)
Indicates the specific date and time at which the President of India officially begins their term in office.
-
D.
officeStartTime (President of Mexico)
Indicates the time at which the President of Mexico officially begins their term in office.
-
E.
officeStartTime (President of Nigeria)
Indicates the date and time at which the President of Nigeria officially begins their term in office.
- 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_69f3494b9fc48190bb61c955ba471275 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff49f888348190b9c55afa73b99e6a |
completed | May 9, 2026, 2:51 p.m. |
| PD | Predicate disambiguation | batch_69ff49614ef88190ac70b034c55ad738 |
completed | May 9, 2026, 2:49 p.m. |
| PDg | Predicate description generation | batch_69ff49f7db2c819094d488d13985334c |
completed | May 9, 2026, 2:51 p.m. |
Created at: May 1, 2026, 1:22 a.m.