Triple
T7843310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Clement of Ancyra |
E181855
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Clement |
E20592
|
NE 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: Clement | Statement: [Saint Clement of Ancyra, hasGivenName, Clement]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clement Context triple: [Saint Clement of Ancyra, hasGivenName, Clement]
-
A.
Clement
chosen
Clement is a given name of Latin origin meaning "merciful" or "gentle," historically borne by several popes and saints.
-
B.
Nicola
Nicola is a given name used in various European languages, often as a variant of Nicholas.
-
C.
Clemens Romanus
Clemens Romanus, better known as Clement of Rome, was a first-century Christian leader traditionally regarded as one of the earliest popes and the author of an influential letter to the Corinthians.
-
D.
Marcellino
Marcellino is an Italian given name, typically used as a diminutive or affectionate form of Marcello.
-
E.
Celso
Celso is a small village in southern Italy that serves as a frazione (hamlet) of the municipality of Pollica in the Campania region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca8285d6488190a95d4c02d7354b53 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb163b32688190b463a9cd8fa3c690 |
completed | March 31, 2026, 12:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5aded4048190b18604963784352c |
completed | March 31, 2026, 5:25 a.m. |
Created at: March 30, 2026, 4:48 p.m.