Triple
T36785357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al Giardello |
E908891
|
entity |
| Predicate | departmentRank |
P34138
|
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: [Al Giardello, departmentRank, lieutenant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: departmentRank Context triple: [Al Giardello, departmentRank, lieutenant]
-
A.
rankWithinOrganization
chosen
Indicates the relative hierarchical position or level an entity holds within a specific organization.
-
B.
depthRank
Indicates the relative ordering of entities based on how deep or distant they are along a specified depth dimension or hierarchy.
-
C.
classRank
Indicates the relative academic standing or position of an entity within a class or cohort based on performance or criteria.
-
D.
divisionRank
Indicates the hierarchical position or level an entity holds within a particular division or organizational subdivision.
-
E.
attendanceRank
Indicates the relative position or level of an entity in terms of how frequently or consistently it attends compared to others.
- 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_69f76e7a937c81909ed7359641e670f6 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7ca93bd0481909d6eee9e950001a1 |
completed | May 3, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69f7c89b528c8190bf80b230fc7c7108 |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:12 p.m.