Triple
T1573663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naval Base Point Loma |
E33597
|
entity |
| Predicate | hasSecurityClassification |
P406
|
FINISHED |
| Object | restricted military area |
—
|
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: restricted military area | Statement: [Naval Base Point Loma, hasSecurityClassification, restricted military area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecurityClassification Context triple: [Naval Base Point Loma, hasSecurityClassification, restricted military area]
-
A.
securityClassification
chosen
Indicates the level or category of security sensitivity or access restriction assigned to an entity.
-
B.
hasTypeOfSecrecy
Indicates that something is associated with a particular kind or level of secrecy.
-
C.
governmentClassification
Indicates that an entity is assigned a specific status or category according to a government’s official classification system.
-
D.
hasSecurityRelationship
Indicates a relationship in which one entity provides, manages, or is otherwise linked to the security or protection of another entity.
-
E.
hasLCClassification
Indicates that an entity is assigned a specific Library of Congress Classification code representing its subject or shelving category.
- 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_69a885f27a4c8190a4622252cdf54c00 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a96083e7308190abbf025fe8e43abb |
completed | March 5, 2026, 10:52 a.m. |
| PD | Predicate disambiguation | batch_69a907ba63c88190b60c14dec8d1e40f |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:27 p.m.