Triple
T7849617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Perimeter |
E182010
|
entity |
| Predicate | hasLocalTerm |
P70766
|
FINISHED |
| Object | inside the Perimeter |
—
|
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: inside the Perimeter | Statement: [The Perimeter, hasLocalTerm, inside the Perimeter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalTerm Context triple: [The Perimeter, hasLocalTerm, inside the Perimeter]
-
A.
hasLocalExpression
chosen
Indicates that something has a specific form, representation, or manifestation that is valid or defined only within a particular local context or region.
-
B.
hasTerm
Indicates that an entity includes, is associated with, or is defined by a specific term or condition.
-
C.
hasLocalLevel
Indicates that one entity possesses, is associated with, or is defined at a specific local administrative or organizational level relative to another entity.
-
D.
hasLocalCharacter
Indicates that something possesses qualities, features, or significance that are specific to a particular locality or region.
-
E.
hasCanonicalTerm
Indicates that one term in a set is designated as the standard or authoritative form used to represent a concept or 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_69ca82869ee08190b8f9040dbc2c0467 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb18e989ac819090e459b77d8932d3 |
completed | March 31, 2026, 12:44 a.m. |
| PD | Predicate disambiguation | batch_69cae92180f88190ae3d44c3de7adc93 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:50 p.m.