Triple
T18445199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | County of Edessa |
E450636
|
entity |
| Predicate | firstLatinStateInEast |
P16319
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [County of Edessa, firstLatinStateInEast, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstLatinStateInEast Context triple: [County of Edessa, firstLatinStateInEast, true]
-
A.
firstStateOfTheUnionOf
Indicates that one entity is the first State of the Union address delivered by the other entity (typically a political leader or officeholder).
-
B.
firstCaesarInEast
Indicates that the subject is the earliest or original holder of the title "Caesar" within an eastern region or eastern branch of rule.
-
C.
oldestChristianState
chosen
Indicates that the subject is recognized as the earliest or first established Christian state in comparison to other states.
-
D.
firstConstitutedIn
Indicates the time or context in which an entity (such as an organization, body, or structure) was originally formed or formally established.
-
E.
foundingState
Indicates that a state or entity played a primary role in establishing or creating another organization, institution, or political 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_69d8d38345688190b565eac2e4cd7935 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e51c15127881909d23b6dd45d7ccc9 |
completed | April 19, 2026, 6:16 p.m. |
| PD | Predicate disambiguation | batch_69e469c943a4819094c8fdc5971ad3a7 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:30 a.m.