Triple
T10581921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Museo Soumaya Plaza Carso |
E249755
|
entity |
| Predicate | numberOfFaçadePanels |
P40883
|
FINISHED |
| Object | about 16,000 hexagonal tiles |
—
|
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: about 16,000 hexagonal tiles | Statement: [Museo Soumaya Plaza Carso, numberOfFaçadePanels, about 16,000 hexagonal tiles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFaçadePanels Context triple: [Museo Soumaya Plaza Carso, numberOfFaçadePanels, about 16,000 hexagonal tiles]
-
A.
numberOfPanels
chosen
Indicates the total count of distinct panels associated with or contained within a given entity.
-
B.
numberOfStainedGlassPanels
Indicates the count of stained glass panels associated with a given entity or object.
-
C.
hasNumberOfInscribedPanels
Indicates the relationship that specifies how many inscribed panels are associated with a given entity.
-
D.
numberOfGlassPanes
Indicates the quantity of individual glass panes associated with or contained in an object or structure.
-
E.
façadeType
Indicates the specific kind or style of façade that characterizes or is applied to a building or structure.
- 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_69d381c9d3d48190a29ee491e1696a0e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d52766d53c8190b51753768ab58c31 |
completed | April 7, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69d51907b2b881908ab9a8594688ee06 |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:39 p.m.