Triple
T11148795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Syria–United States relations |
E263732
|
entity |
| Predicate | caesarActEnactmentYear |
P98072
|
FINISHED |
| Object | 2019 |
—
|
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: 2019 | Statement: [Syria–United States relations, caesarActEnactmentYear, 2019]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caesarActEnactmentYear Context triple: [Syria–United States relations, caesarActEnactmentYear, 2019]
-
A.
appointedCaesarYear
Indicates the year in which an individual was appointed to the position or title of Caesar.
-
B.
dateOfCaesarAppointment
Indicates the date on which an individual was appointed to the position or title of Caesar.
-
C.
firstConsulshipYear
Indicates the calendar year in which an entity held its first consulship or began serving its first term as consul.
-
D.
praetorshipYear
Indicates the specific year in which an entity held or exercised the office or role of praetor.
-
E.
tribunateYear
Indicates the year in which a person held or exercised the office of tribune.
- 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8701ea481908c86c2359f5dc957 |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75ce71944819089eee9b5c9283cbd |
completed | April 9, 2026, 8:01 a.m. |
| PDg | Predicate description generation | batch_69d7706116248190a87440bec3960884 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:28 p.m.