Triple
T1989287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Police Academy (Egypt) |
E43213
|
entity |
| Predicate | hasRankUponGraduation |
P35205
|
FINISHED |
| Object | police 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: police lieutenant | Statement: [Police Academy (Egypt), hasRankUponGraduation, police lieutenant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRankUponGraduation Context triple: [Police Academy (Egypt), hasRankUponGraduation, police lieutenant]
-
A.
hasDegree
Indicates that an entity possesses or has been awarded a specific academic or professional degree.
-
B.
graduatedWithHonors
Indicates that an entity completed an academic program with a distinction or honors-level achievement according to the institution’s criteria.
-
C.
hasGraduateDivision
Indicates that an institution or academic unit possesses an official graduate-level division or administrative body responsible for graduate programs.
-
D.
academicStatus
Indicates the educational or scholarly standing or level an entity holds within an academic context.
-
E.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
- 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_69a88714cf2c819081644be450b8356e |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8ee02dc81908fec9fd8df7a4f40 |
completed | March 7, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69abb79ad6888190be99943a9c73cf3e |
completed | March 7, 2026, 5:28 a.m. |
| PDg | Predicate description generation | batch_69abb8ec608c81908917e945e0118ac4 |
completed | March 7, 2026, 5:34 a.m. |
Created at: March 4, 2026, 7:37 p.m.