Triple
T17039060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DSACEUR |
E413395
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | SHAPE |
E115880
|
NE 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: SHAPE | Statement: [DSACEUR, locatedIn, SHAPE]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SHAPE Context triple: [DSACEUR, locatedIn, SHAPE]
-
A.
SHAPE
chosen
SHAPE is the central military command headquarters of NATO responsible for planning and executing the alliance’s collective defense operations in Europe.
-
B.
Shape
Shape is a health and fitness magazine and digital brand focused on exercise, nutrition, and wellness content, owned by Dotdash Meredith.
-
C.
The Shape
The Shape is the silent, masked embodiment of pure evil and the primary antagonist in John Carpenter’s Halloween horror film franchise.
-
D.
Formas
Formas is a Swedish government research council that funds research in the areas of environment, agricultural sciences, and spatial planning.
-
E.
shape operator
The shape operator is a linear map in differential geometry that describes how a surface curves in different directions by relating changes in its normal vector to directions in the tangent plane.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d886cd18288190b006abab23f811b7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d8f45f84819092cfb27cc33da026 |
completed | April 18, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a011b5ceb048190a7f6cf2361360f90 |
completed | May 10, 2026, 11:57 p.m. |
Created at: April 10, 2026, 5:33 a.m.