Triple
T28375583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarge's Surplus Hut |
E718746
|
entity |
| Predicate | hasExteriorDesign |
P43197
|
FINISHED |
| Object | Quonset hut with military theming |
—
|
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: Quonset hut with military theming | Statement: [Sarge's Surplus Hut, hasExteriorDesign, Quonset hut with military theming]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExteriorDesign Context triple: [Sarge's Surplus Hut, hasExteriorDesign, Quonset hut with military theming]
-
A.
hasExteriorStyle
chosen
Indicates that an entity possesses or is characterized by a particular exterior design or stylistic appearance.
-
B.
hasExteriorType
Indicates that an entity possesses a specific kind or style of exterior.
-
C.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
D.
exteriorShape
Indicates the overall outer form or contour that characterizes how something appears from the outside.
-
E.
hasFullCarDesignation
Indicates that an entity is associated with a complete, formal car designation (such as full model name or code) rather than a partial or abbreviated identifier.
- 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_69eff6ee5afc8190bd7375a29f0cc6c6 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f6b903538481909cffcb6cc1cc0e70 |
completed | May 3, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69f6b626120c819097c9ad04487570d7 |
completed | May 3, 2026, 2:42 a.m. |
Created at: April 28, 2026, 1:03 a.m.