Triple
T30883993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Legio XVIII |
E786704
|
entity |
| Predicate | symbolicConsequence |
P113484
|
FINISHED |
| Object | legion number never used again by Rome |
—
|
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: legion number never used again by Rome | Statement: [Legio XVIII, symbolicConsequence, legion number never used again by Rome]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: symbolicConsequence Context triple: [Legio XVIII, symbolicConsequence, legion number never used again by Rome]
-
A.
hasConsequence
Indicates that one event, action, or condition leads to or results in another as its outcome or effect.
-
B.
consequenceOfInfluence
Indicates that one event, state, or condition occurs as a result of the influence or impact exerted by another.
-
C.
consequenceInText
Indicates that one event, action, or state is presented in the text as a consequence or result of another.
-
D.
hasConsequenceHypothesis
Indicates that one situation, event, or statement is hypothesized to lead to or imply a particular consequence.
-
E.
interpretiveConsequence
chosen
Indicates that one entity is a conclusion, implication, or interpretive outcome that follows from 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_69f224bae17c8190bb3a6a28e3d019df |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6a0ea04888190ac3a813b603bcb5c |
completed | May 3, 2026, 1:12 a.m. |
| PD | Predicate disambiguation | batch_69f69fe463248190aa78128abeab1183 |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 29, 2026, 8:48 p.m.