Triple
T1953013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cassio |
E42200
|
entity |
| Predicate | losesPositionAs |
P33488
|
FINISHED |
| Object | lieutenant |
—
|
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: lieutenant | Statement: [Cassio, losesPositionAs, lieutenant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: losesPositionAs Context triple: [Cassio, losesPositionAs, lieutenant]
-
A.
namedAfterPosition
Indicates that an entity is named after a specific position, role, or rank associated with it.
-
B.
tookPositionOn
Indicates that an entity expressed or adopted a specific stance, opinion, or viewpoint regarding a particular issue, topic, or subject.
-
C.
ownerPosition
Indicates the spatial or positional relationship of an owner relative to the owned entity.
-
D.
hasPositionOn
Indicates that one entity occupies or holds a specific role, job, or spatial location relative to another entity.
-
E.
appliesToPosition
Indicates that something (such as a rule, condition, or attribute) is relevant or applicable to a specific position or role.
- 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_69a8870eea088190a38781990812a9bc |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb3501d108190bc5cb23f53db4411 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abaff3eda88190b643994cb4dfb8df |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb1ddccbc8190bf2bd8bac673c0c5 |
completed | March 7, 2026, 5:04 a.m. |
Created at: March 4, 2026, 7:36 p.m.