Triple
T35861869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Licinii (by adoption) |
E1036972
|
entity |
| Predicate | usesNomen |
P153012
|
FINISHED |
| Object | Licinius |
—
|
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: Licinius | Statement: [Licinii (by adoption), usesNomen, Licinius]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesNomen Context triple: [Licinii (by adoption), usesNomen, Licinius]
-
A.
hasNoun
Indicates that an entity possesses or is associated with a specific noun as an attribute, label, or grammatical component.
-
B.
praenomenOrNomen
chosen
Indicates that the related name element functions either as a personal given name (praenomen) or as a family/clan name (nomen) within a naming system.
-
C.
usesNameDueTo
Indicates that one entity adopts or applies a particular name for another entity specifically because of some motivating reason, circumstance, or dependency.
-
D.
usesNamingSystem
Indicates that one entity adopts or applies a particular naming system or convention to identify or label other entities.
-
E.
usesNameForm
Indicates that one entity adopts or applies a particular standardized form or variant of a name associated with another 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_69f76e1d279c8190843e5b64a0a12c3f |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aa3883d48190b05e3d2da7a017ae |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d435288190b30b1991fb003121 |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 3, 2026, 4:06 p.m.