Triple
T5638884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carmel Mission Museum |
E124215
|
entity |
| Predicate | usesBuildingMaterial |
P1272
|
FINISHED |
| Object | adobe |
—
|
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: adobe | Statement: [Carmel Mission Museum, usesBuildingMaterial, adobe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesBuildingMaterial Context triple: [Carmel Mission Museum, usesBuildingMaterial, adobe]
-
A.
usesBuilding
Indicates that one entity makes use of, occupies, or operates within a particular building.
-
B.
materialUsed
chosen
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
C.
constructionUsed
Indicates that one entity was employed as a construction method, material, or component in creating or assembling another entity.
-
D.
hasStationBuildingMaterial
Indicates that a station’s building is constructed from, or primarily composed of, a specified material.
-
E.
usesMortar
Indicates that one entity employs or applies mortar in relation to another entity or context.
- 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_69c00824643c81909ffdb888a2d35189 |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c02283bb248190b29ac6255c78c5ec |
completed | March 22, 2026, 5:10 p.m. |
| PD | Predicate disambiguation | batch_69c01b2168508190b64b355cf50034ad |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:41 p.m.